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Multiple attribute decision making: Methods and applications
... Typical examples of such analytical MCDM techniques are the technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP). As an MCDM technique, TOPSIS, which was developed by [52] for the optimal selection of the best alternative solution given a finite number of criteria, provides a simultaneous ranking of the alternatives in order of their relative distances A study by [34] used the Ashby charts for the selection of plant-fiber-reinforced plastics for product design and improvement as alternatives to glass fiber composites and demonstrated the tool's robust capabilities in assessing the mechanical properties of materials, the processing methods applicable to each material and how each material's eco impact compares with those of other materials. Readers may refer to the following literature for additional use cases of the ANSYS Granta and Ashby plots for material selection [49][50][51]. ...
... Typical examples of such analytical MCDM techniques are the technique for order preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP). As an MCDM technique, TOPSIS, which was developed by [52] for the optimal selection of the best alternative solution given a finite number of criteria, provides a simultaneous ranking of the alternatives in order of their relative distances from the positive ideal and negative ideal solutions. These distances are calculated using mathematical equations, numerical values of the considered criteria and weights assigned to the decision criteria based on expert judgement. ...
... These distances are calculated using mathematical equations, numerical values of the considered criteria and weights assigned to the decision criteria based on expert judgement. On the other hand, AHP, which was introduced by [52,53], provides a simple structured solution to decision-making challenges. In this process, a pairwise comparison of the alternatives is developed and checked for accuracy through a consistency ratio. ...
Portland cement is the primary barrier material for well abandonment. However, the limitations of cement, especially under harsh downhole conditions, are necessitating research into alternative barrier materials. While several alternatives have been proposed, the screening process leading to their selection is scarcely discussed in the literature, resulting in the non-repeatability of the selection process. This study develops a dynamic multi-criteria decision-making technique for assessing the material options for the abandonment of high-pressure high-temperature (HPHT) wells with exposure to harsh reservoir fluids. The material screening process is performed in ANSYS Granta and a combined technique for order of preference by similarity to ideal solution (TOPSIS) and analytical hierarchy process (AHP) approach is used for ranking the shortlisted material alternatives based on seven material properties proven in the literature to be critical to the long-term integrity of well barrier materials. Nine alternative materials are ranked against Portland cement and high alumina cement. The results show that the top-ranking materials are from the phenol formaldehyde and polyamide–imide groups. Of these, the primary production CO2 of the polyamide–imide is, on average, about 25 times higher than the primary production CO2 of the phenol formaldehyde material. A sensitivity analysis of the methodology confirms that the criteria with the highest initial weights are the most impactful in terms of the final rank. The material property values also have an impact on the extent to which variations in their weights affect the hierarchical position of the materials in the TOPSIS-AHP analysis. Despite their higher cost per unit volume, the alternative materials consistently outperformed cement—even when average price was weighted more heavily than the most influential mechanical property.
... A Decision Support System (DSS) serves as an effective solution to assist in complex decision-making processes. A DSS allows for multicriteria data processing and supports systematic and objective evaluation of alternatives [2] [6]. One of the widely used methods in DSS is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). ...
... This method works by identifying the alternative closest to the positive ideal solution and furthest from the negative ideal solution. TOPSIS is popular for its ability to provide clear and measurable results in the form of rankings [2] [4]. TOPSIS has been widely implemented in various contexts, including the selection of social assistance recipients in Kutai Kartanegara, the selection of livestock housing locations, and decision-making in the fisheries sector. ...
East Flores Regency is one of the regions in Indonesia that has great potential in the marine and fisheries sector. With most of its people relying on fishing activities, the provision of fishing boat assistance is one of the local government's priority programs to improve the welfare of coastal communities. The purpose of this research is to design and develop a Decision Support System (SPK) that can help the Fisheries and Maritime Affairs Office in determining prospective recipients of fishing boat assistance objectively and on target. The method used in this research is Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is able to process multicriteria data such as income, age, number of dependents, and boat condition. This method was chosen for its superiority in ranking alternatives based on their proximity to positive and negative ideal solutions. The results show that the developed system is able to generate a ranking of beneficiaries based on the level of eligibility, thus accelerating the decision-making process and increasing transparency and accuracy in the selection of beneficiaries. The implementation of this system is expected to not only support operational efficiency, but also contribute to improving the welfare of traditional fishermen in the region.
... multiple, often conflicting, criteria such as cost, environmental impact, and social value, providing a structured and transparent framework for setting innovation priorities [5,6]. ...
... Originally developed by Saaty [6], AHP is a structured MCDM method designed to facilitate complex evaluations involving both qualitative and quantitative inputs. Its hierarchical structure enables DM to decompose a complex problem into a set of interrelated decision elements, including objectives, criteria, sub-criteria, and alternatives [5,30]. ...
Sustainability is a key focus for the machinery manufacturing industry, aiming to align innovation with environmental and economic goals. This research proposes an Analytic Hierarchy Process (AHP)-based framework to evaluate and rank sustainability-focused innovation criteria. The model was validated using 54,054 projects from CORDIS and TÜBİTAK and a survey of 46 experts from academia, industry, and the public sector. According to AHP results, Economic Criteria ranked highest (46%), followed by Product-Related Environmental (18%), Market (16%), Process-Related Environmental (13%), and Social Criteria (7%). Product Cost (45%), Elimination of Hazardous Substances (30%), and Occupational Health and Safety (29%) ranked highest among sub-criteria, reflecting the dominance of financial and regulatory priorities. Social and process-related criteria were less prioritized unless linked to regulatory compliance. The framework provides a practical tool for innovation leaders and policymakers aiming to embed sustainability in strategic planning. It aligns with global initiatives like the Paris Agreement and the European Green Deal, contributing to both theory and practice in industrial sustainability.
... While the origins of multi-criteria thinking date back centuries, most of the well-known Multi-Criteria Decision Making (MCDM) tools such as ELECTRE [28], AHP [29], TOPSIS [30] and PROMETHEE [31] emerged in the second half of the 20th century [32], [33], [34]. ...
... Sustainability is a natural subject of MCDM, because, by itself, it includes three sub-sets of criteria: economics, environmental, and social aspects [36], [37]. It is designed to support optimal decision-making by simultaneously evaluating multiple criteria and viewpoints [30], [38], [39]. Objective MCDM methods are known for their computational efficiency, while subjective methods prioritize the inclusion of decision-makers' preferences in a transparent manner. ...
Sustainable Development Goals (SDGs) were set in 2015 by the UN General Assembly to achieve global economic, social, ecological development until 2030. The Balkan Region in the Southeastern Europe have also accepted these goals. Ten countries in the region have similar geographic, environmental and economic features. This paper aims to compare the progress of Balkan countries in achieving the SDGs by employing a novel Multi Criteria Decision Making (MCDM) model named as "LR". This hybrid model is an integration of six MCDM methods to evaluate better the SDGs progress of Balkan countries than a traditional method. Criterion weights are determined by LOPCOW, LMAW and LBWA and the ranking is made by RAFSI, RAPS and RAWEC methods. As the outcome of the novel LR model, the SDG 1 is the most significant criterion out of 17 goals while Croatia is the best performer among ten Balkan countries in achieving the SDGs.
... MCDM provides a structured framework for evaluating complex environmental decisions involving multiple, often competing, criteria [5]. By integrating RS/GIS with MCDM, stakeholders can derive spatially optimized solutions that balance ecological, economic, and social considerations [6]. ...
... Results guided policy interventions in drought-prone areas. 6. RESULTS AND ANALYSIS ...
Sustainable water resource management is a critical challenge in the face of increasing population pressure, climate change, and environmental degradation. The integration of remote sensing (RS) data with Multi-Criteria Decision-Making (MCDM) techniques has emerged as a powerful approach to support informed and spatially explicit decision-making in this domain. This paper presents a comprehensive review and analytical framework that combines RS-derived geospatial data with widely used MCDM methods such as Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and VIKOR. We examine how these integrated methodologies enhance the accuracy, objectivity, and scalability of water resource planning and management. Through a detailed methodology section, case study applications, and comparative analysis, we demonstrate the effectiveness of integrating RS and MCDM in identifying groundwater potential zones, flood-prone areas, and optimal locations for water harvesting structures. The paper also discusses challenges, validation strategies, and future research directions. Our findings underscore the importance of interdisciplinary approaches in achieving sustainable water governance.
... TOPSIS, developed by Hwang and Yoon (1981), solves the MCDM problem based on the concept that the selected alternative should have the smallest distance to the positive ideal solution and the longest distance from the negative ideal solution. The positive ideal solution optimizes functionality while minimizing cost, whereas the negative ideal solution maximizes cost while minimizing functionality. ...
... The positive ideal solution optimizes functionality while minimizing cost, whereas the negative ideal solution maximizes cost while minimizing functionality. The detailed procedure of TOPSIS can be found in the study done by Hwang and Yoon (1981 ...
The selection of an appropriate advertising platform, based on personalized preferences, is considered as a multiple criteria decision-making (MCDM) problem which involves assessment of a set of advertising platforms (alternatives) in terms of preferences (decision criteria). This study proposes a MCDM model to determine optimal advertising platform. The Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are integrated to determine the best decision alternative under MCDM environment. The developed model is applied to a case study, which considers a decision matrix established with 11 advertisement platforms (decision alternative) dominating each-other based on their 7 attributes (decision criteria). The relative weights of all criteria are determined, which are then supplied to TOPSIS methodology to rank the advertisement platforms.
... AHP's hierarchical structure and pairwise comparison mechanism provided a systematic approach for handling multiple criteria and subjective judgments in manufacturing decision-making contexts. Subsequent research by Hwang and Yoon (1981) introduced the TOPSIS methodology, which became another cornerstone technique for manufacturing process selection problems. ...
... Lee.K.M [7] familiarized the bipolar vague fuzzy sets which are a delay of fuzzy sets. TOPSIS method was established by Hwang.C.L. and Yoon.K [6] is a famous in multi criteria decision making method. Chen, Hong.D.H and Choi.C.H [2,3,4] done their studies in multiple attribute decision making problems in fuzzy and vague set theory. ...
In this paper we describe the concept of bipolarity on vague sets. We develop a bipolar vague VIKOR Method with multi-criteria decision-making problems in which the ranking order of the alternatives are engaged as bipolar vague sets. Lastly a mathematical illustration is given to demonstrate the purpose and efficiency of the established bipolar vague VIKOR method using MATLAB. Index Terms-Bipolar vague set, VIKOR method and multi-criteria decision-making.
... This study presents an integrated decision-support framework that bridges material science, structural mechanics, optimisation theory, and environmental systems engineering to develop zero-waste packaging solutions. The research is rooted in four interdependent pillars: a. Material Preselection Using Hybrid MCDM: Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were employed to screen potential bio-based materials based on mechanical, economic, and environmental criteria, ensuring that preliminary candidates align with performance thresholds and sustainability benchmarks (Saaty, 2008;Hwang & Yoon, 1981 In sum, this work not only validates bio-based packaging materials from a structural and sustainability standpoint but also proposes a decision-making roadmap for scalable, low-impact packaging solutions tailored for the FMCG industry and beyond. ...
The environmental burden from plastic and mixed-material waste in fast moving consumer goods (FMCG) packaging has intensified the demand for zero-waste alternatives that balance mechanical performance, sustainability, and cost. This study develops an industrial engineering based framework for selecting and validating such packaging solutions. A multi-stage methodology integrates Analytic Hierarchy Process (AHP) and TOPSIS for material screening, emphasising mechanical strength (40%), environmental performance (30%), cost (20%), and processability (10%). PLA, recycled corrugated cardboard, and sugarcane bagasse emerged as top candidates, with PLA scoring 0.826 on TOPSIS. Finite Element Analysis (FEA) validated structural integrity under a 100 N axial load across different geometries. Multi-objective optimisation using NSGA-II identified Pareto-optimal solutions balancing compressive strength, cost, and global warming potential (GWP). A Life Cycle Engineering (LCE) approach assessed cradle-to-grave environmental impacts, including cumulative energy demand (CED), carbon emissions, eutrophication, and fossil resource depletion. PLA packaging achieved 6.1 MPa compressive strength, 3.2 MPa maximum von Mises stress, and 0.021 strain, outperforming PET and corn-starch-based composites. It reduced unit cost by 23% ($0.038) and GWP by 35.6% (0.72 kg CO₂-eq) compared to PET. LCE analysis showed 48% lower CED and 41% lower eutrophication. A Sustainability Performance Index (SPI: 0.42–0.88) ranked PLA-based shell structures highest for their mechanical environmental trade-offs. The integrated framework effectively supports scalable, zero-waste packaging development.
... Due to its clarity and efficiency, the TOPSIS method has proven to be a powerful tool for addressing MAGDM problems. Initially proposed by Hwang and Yoon [22] in 1981, the TOPSIS method ranks evaluation objects by measuring their distances from the ideal and negative ideal solutions. Building on this foundation, Thilagavathy et al. [23] developed SF Heronian mean aggregation operators and integrated them with the TOPSIS method to solve practical group decision-making (GDM) problems in SF environments. ...
The spherical fuzzy set is a generalization of various fuzzy structures, including fuzzy sets, intuitionistic fuzzy sets, Pythagorean fuzzy sets, and picture fuzzy sets. The notion of the spherical fuzzy chi-square divergence measure was defined by the intuitionistic fuzzy chi-square divergence measure. In this paper, the concept of the chi-square divergence measure for spherical fuzzy sets is defined and some operational properties related to the definition are proposed. In addition, comparative analysis is conducted through simulation experiments and numerical examples with common distance measures and similarity measures. Based on this, a multiple-attribute group decision-making (MAGDM) method based on the TOPSIS method is proposed. Finally, the feasibility and reliability of the method are verified through an example of evaluating a food distribution center.
... TOPSIS was originally proposed by Hwang and Yoon (1981) based on the concept that the chosen alternative should have the shortest distance from the ideal solution and the farthest from the negative ideal solution. TOPSIS considers the distances to both the ideal and the negative-ideal solutions simultaneously by taking the relative closeness to the ideal solution. ...
Introduction
Fishing harbor cities often face decline due to the depletion of fishing resources. In response, this study aims to develop an expert evaluation system to assist in transitioning these harbors toward sustainable sailing-yacht tourism. Such a transition aligns with the objectives of Sustainable Development Goals (SDGs) 14 (Life Below Water) and 11 (Sustainable Cities and Communities).
Methods
To construct the evaluation framework, the Analytical Network Process (ANP) was used to determine the interdependent relationships among criteria, while the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was applied to rank and prioritize alternatives. This integrated approach facilitated a comprehensive evaluation model for sustainability transitions in harbor redevelopment.
Results
An empirical case study conducted in the Asia-Pacific region demonstrated the application of the expert system in selecting an ideal fishing harbor for redevelopment. The combined ANP-TOPSIS model effectively identified the most suitable harbor by systematically analyzing multiple dimensions related to sustainable tourism development.
Discussion
This research contributes to the planning and development of sustainable harbors, urban areas, and sailing-yacht tourism. It offers a comprehensive evaluation model grounded in expert decision-making methods. Furthermore, the findings suggest that fishing harbors, especially those in archipelagic regions, possess significant potential for transformation into sustainable sailing-yacht tourism destinations, supporting broader SDG implementation efforts.
... The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method, proposed by Hwang and Yoon (1981), orders alternatives based on the shortest distance from the positive ideal solution and the longest distance from the negative ideal solution. It begins with the construction of a decision matrix, followed by normalization to eliminate discrepancies between criteria (Behzadian et al., 2012). ...
Objective: To present an applied study to identify and propose logistics indicators that help reduce the vulnerabilities of indigenous communities in the South and Southeast of Pará, supporting more effective public policies adapted to the local reality. Theoretical Framework: Addresses the logistical difficulties of these communities, such as geographic barriers, precarious infrastructure and limited access to essential services. Method: Research based on bibliographic review, document analysis and case study, focusing on mapping vulnerabilities and developing relevant indicators for logistics management using methods such as VFT, TOPSSIS. Results and Discussion: A conceptual model was developed with indicators such as proximity to health units and transportation routes, which allow monitoring and improving access to essential resources. Research Implications: The indicators created are useful tools for planning and implementing logistics public policies that reduce vulnerabilities and improve access to services in indigenous communities. Originality/Value: The study presents a proposal adapted to the specificities of the South and Southeast of Pará, contributing with an innovative model for future research and actions in similar regions.
... In the context of groundwater potential mapping, these methods have been applied to prioritize locations for well siting, artificial recharge, and aquifer protection [7]. Comparative studies suggest that hybrid approaches combining GIS with MCDM yield more reliable results than standalone methods [8]. ...
Groundwater is a critical component of global freshwater resources, especially in regions facing increasing water demand due to population growth and climate variability. Effective groundwater management requires accurate identification of potential zones for recharge and extraction. This paper presents an integrated approach using Geographic Information Systems (GIS) and Multi-Criteria Decision-Making (MCDM) techniques to delineate groundwater potential zones. The methodology combines spatial data layers such as lithology, slope, land use/land cover, drainage density, lineament density, rainfall, and depth to water table within a GIS environment. Analytical Hierarchy Process (AHP), Simple Additive Weighting (SAW), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are employed to assign weights to thematic layers and derive a Groundwater Potential Index (GWPI). The model is validated using borewell yield data and Receiver Operating Characteristic (ROC) curve analysis. Results indicate that high-potential zones are primarily located in alluvial and fractured rock formations with favorable topographic and hydrological conditions. This study demonstrates the effectiveness of GIS-MCDM integration in supporting sustainable groundwater resource planning and management.
... A restriction on the available budget for each planning period is shown using (22), which ensures that the Total Cost (i.e., Eq. (1)) cannot go beyond the predetermined budget for the time horizon. (23) and (24) both present non-negativity requirements on decision variables. ...
... Constraints (15) and (16) pledge that in regular time and overtime, the machine capacity is assured. ...
The focus of Aggregate Production Planning (APP), a type of medium-term planning, is on the most economical way to manage
production in order to meet fluctuating demand and other uncertainties like production loss as it affects productivity. The proposed
method deals on checking the impact of production loss on inventory and labor levels, overtime, backordering levels, workforce, machine,
and warehouse capacity in an effort to reduce total costs and repair cost and maximize income. The study results were obtained using
Lingo version 18 software at the very end using data gathered from Rich Pharmaceuticals Limited (RPL). Four different scenarios were
thought of for the suggested model, each of which produced a useful compromise solution and varying degrees of DM satisfaction with
the various fuzzy objective values. Thanks to the suggested model's systematic structure for facilitating decision-making, a decision maker
can interactively change the fuzzy data and associated model parameters until a satisfying answer is attained in the quest to reduce
production loss.
Key Words: Production Loss, Workforce, goal programing, Decision maker, linear membership function
... Based on a comparative analysis of these methodologies, this study adopts a hybrid model, the TOPSIS-Entropy Weight Method, which integrates the comprehensive sorting capability of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) with the objective weight assignment advantages of the Entropy Weight Method [23]. The innovation of this model lies in the following: TOPSIS constructs positive and negative ideal solutions and calculates the relative closeness of evaluation objects to these solutions, ensuring mathematically rigorous interpretability and operational feasibility; the Entropy Weight Method assigns weights based on the dispersion degree of indicator data, thereby effectively avoiding interference from subjective factors [24]. ...
By constructing a comprehensive evaluation index system for the development level of Agricultural Machinery Socialization Services (AMSS) in China’s hilly and mountainous areas, the article adopts the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) entropy weight method to carry out a comprehensive evaluation of the development level of AMSS in China’s 17 major hilly mountainous provinces, and utilizes the obstacle degree model and the Dagum Gini coefficient decomposition method to deeply explore the developmental constraints and regional differences in characteristics. The results of the study show that the development level of AMSS in all provinces is generally on the rise, and the overall development level of the Southwest region is relatively lagging behind, with significant differences from other regions. The obstacle degree model shows that industrial development, Government funding, and farmland construction are the main factors constraining AMSS in hilly and mountainous areas, specifically, the degree of coverage of AMSS, the percentage of agricultural machinery professional cooperatives, the degree of land fragmentation, and the level of agricultural machinery extension inputs have a greater impact on the level of development of AMSS. Dagum Gini coefficient calculations show that the overall relative differences in development levels have a tendency to decrease, but the level of development of agricultural machinery socialization in the southwestern hilly and mountainous second-maturity areas is still low, with an imbalance in development within the region and a more significant gap with the development levels of other hilly and mountainous regions.
... After calculating the normalized decision matrix, the weighted sum calculation is performed. This involves multiplying the normalized values by the weights of each criterion ( ) and summing the results according to the following equation (Hwang & Yoon, 1981): ...
This study identifies the optimal route for transporting agricultural fruits using the Simple Additive Weighting (SAW) method within a Multicriteria Decision-Making (MCDM) framework. Data was gathered through a literature review on transportation principles, route selection criteria, and truck routes, identifying eight critical factors for route selection. Transportation route data were also systematically collected, forming the basis of the proposed conceptual framework. The SAW analysis identified the highest-scoring routes for each segment: Route A1 (6.35406), Route B1 (6.38532), Route C1 (6.26248), and Route D3 (5.29061). Historical data from the past five years confirmed consistency in route selection. Comparatively, Dijkstra's Algorithm, based on single factors like distance, time, or cost, proved less effective for agricultural transportation. In contrast, the SAW method, integrating multiple factors, ensured more accurate route selection. Key influencing factors included road conditions, infrastructure or road width, and facility availability. The optimal route from Thailand to China was Route A1-B1, passing through Chanthaburi, Rayong, Chonburi, Chachoengsao, Samut Prakan, Bangkok, Pathum Thani, Ayutthaya, Ang Thong, Sing Buri, Chai Nat, Nakhon Sawan, Phichit, Phitsanulok, Uttaradit, Phrae, Lampang, Phayao, and Chiang Rai, terminating at Chiang Khong Customs Checkpoint. These findings offer practical guidance for planning and decision-making in agricultural transportation routes.
... One of the most common methods in MCDM problems is the TOPSIS method, first proposed in 1981 (Hwang & Yoon, 1981;Çınar, 2010). The TOPSIS method, as in other MCDM 91 methods, can use expert opinions for the selection of decision criteria in the decision-making process. ...
Career choice is a pivotal decision that shapes an individual's professional path and has a profound impact on their life. Various factors influence this process, and identifying and prioritizing these influences in real-world scenarios is often challenging. Ranking the factors that are effective in career choice is a problem that can be handled with Multi-Criteria Decision Making (MCDM) methods. Fuzzy logic approach can be used together with MCDM methods. The concept of Fuzzy Logic was developed by Zadeh (Zadeh, 1965) and fuzzy versions of many MCDM methods have been proposed in this context. This study investigates which fields of study hold greater significance during the career planning and preference stages for statistics department graduates, taking into account the influences they encounter in their career selection process. The relationships between the main criteria were analyzed using the Fuzzy DEMATEL method, based on input from expert decision-makers. Subsequently, an initial table was created using the Fuzzy TOPSIS method, incorporating criteria weights derived from the Fuzzy DEMATEL analysis. This approach enabled the identification of the most appropriate decision alternatives and rankings across five different fields of study. The findings indicate that individuals who choose the statistics department due to factors such as numerical ability, skills, interests, environmental influences and family structure, professional values, psychological needs, earnings potential, ease of job acquisition, coursework, and social opportunities tend to prefer working as data specialists after graduation.
... The utilisation of MADM has garnered considerable attention in contemporary discourse (Bisht and Pal 2024). According to Hwang and Yoon (1981), 17 distinct multi-indicator decision-making methods can be categorised based on their type, significance and the nature of the acquired information. Among these models, TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) stands out as an effective tool in animal science. ...
Background
Eggs provide limited energy and essential nutrients necessary for chicken embryo growth. Intra‐egg nutrition serves as an effective approach to address initial growth constraints during the embryonic stage and post‐hatching.
Objective
This study aimed to identify the optimal levels of L‐valine or L‐tryptophan amino acids administered via in ovo injection to improve the growth performance of Ross 308 broiler chickens.
Methods
Five hundred fertile eggs were weighed and incubated. On Day 14, the fertile eggs were divided into five groups, receiving injections of either 0.95% (Val‐1) or 1.05% (Val‐2) L‐valine, 0.55% (Trp‐1) or 0.60% (Trp‐2) L‐tryptophan, or distilled water (control) at a volume of 0.5 mL. Nine performance criteria, including hatchability, body weight, feed intake, feed efficiency, livability, production index, villus length to crypt depth, Lactobacillus and Escherichia coli populations were assessed as least‐square means.
Results
A multiple‐attribute decision‐making (MADM) method, utilising the technique for order of preference similarity to the ideal solution (TOPSIS), was employed to rank the in ovo amino acid treatments. The treatments yielded the following scores: control (0.7703), Val‐1 (0.4759), Val‐2 (0.4161), Trp‐1 (0.7761) and Trp‐2(0.1509).
Conclusions
The findings indicate that injecting 0.55% L‐tryptophan on Day 14 of incubation is a beneficial strategy to enhance growth performance in broiler chickens.
... MCDM is the evaluation of a finite number of options using a large number of criteria, mostly weighted for the purpose of selection, ranking, classification, prioritization or elimination [10]. ...
Coronavirus, which has spread worldwide and become a pandemic, threatens human health both physically and mentally. Physical threats consist of permanent damage, which is not yet clear, and symptoms such as high fever, shortness of breath experienced by individuals infected with coronavirus. Mental threats, on the other hand, cause fear of coronavirus, that is, coronaphobia and various psychological problems. The purpose of the study is to determine the factors affecting coronaphobia and to reduce or eliminate their effect on people. For this purpose, high priority factors obtained as a result of the ANP method should be examined and studies should be carried out to reduce or eliminate the effects of these factors. In this study, the factors affecting coronaphobia were determined and analyzed in order to reduce and eliminate coronaphobia. This analysis was carried out by the analytical network process (ANP), one of the Multi-Criteria Decision Making (MCDM) methods. According to the priority values obtained as a result of comparing relationships and relationships established by the ANP method; the most important criterion affecting coronavirus fear is the criterion of psychological factors. The most important sub-criteria are weak immune system, hygiene concern and stress disorder, respectively. n this study, the factors affecting coronavirus fear were discussed in general. Among the factors discussed, weighted scores were obtained by establishing bilateral relations using the ANP method. The factors covered in the study consist of 3 main criteria and 14 main criteria covered by these criteria.
... Yöntemin temel prensibi, her bir alternatifin pozitif-ideal çözüme (en iyi değer) ve negatifideal çözüme (en kötü değer) olan uzaklıklarının hesaplanmasına dayanır. Alternatif bir lokasyon, pozitif çözüme ne kadar yakın ve negatif çözüme ne kadar uzaksa, o denli uygun olarak değerlendirilir[1,13].Bu çalışmada, AHP yöntemiyle ağırlıklandırılmış 11 parametreye ait raster veriler her hücre için normalize edilmiştir. Her parametrenin değeri, AHP'den gelen ağırlıklarla çarpılmış ve toplam skorlar hesaplanmıştır. ...
Bu çalışmanın temel amacı, Diyarbakır Ovası’nda yeraltı barajı inşasına uygun alanları belirlemek amacıyla Analitik Hiyerarşi Süreci (AHP) ve TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) gibi çok kriterli karar verme (ÇKKV) yöntemlerinin Coğrafi Bilgi Sistemleri (CBS) ile entegre biçimde uygulanmasıdır. Küresel ölçekte artan su talebi ve mevcut kaynakların sürdürülebilir yönetimi, özellikle yarı kurak bölgelerde alternatif su depolama çözümlerine olan ilgiyi artırmıştır. Yeraltı barajları, bu kapsamda buharlaşma kaybını azaltan ve çevresel etkisi düşük yapılar olarak öne çıkmaktadır. Çalışmada, yeraltı barajı yer seçimi için 11 parametre belirlenmiş ve raster veri formatında CBS ortamında işlenmiştir. Parametreler, 3-6-9 puanlama sistemi ile sınıflandırılmış, AHP yöntemi ile ağırlıklandırılmış ve tutarlılık oranı kontrol edilmiştir. TOPSIS yöntemi kullanılarak her bölgenin uygunluk skorları hesaplanmış ve alanlar “en uygun”, “orta uygun” ve “uygun değil” şeklinde sınıflandırılmıştır. Sonuçlar, özellikle alüvyonal zeminlerin yoğunlaştığı, eğimin düşük ve yüzey su kaynaklarına yakın bölgelerin yüksek uygunluk skorlarına sahip olduğunu göstermiştir. Bu yöntem, sürdürülebilir su yönetimi planlamaları için etkili bir karar destek aracı sunmaktadır.
... The TOPSIS method can be implemented as a set of steps that will be explained below. (Hwang & Yoon, 1981). This method has the objective of ranking alternatives A i (i = 1, 2, …, I) based on certain attributes C j (j = 1, 2, … , J) . ...
Portfolio rebalancing is a critical aspect of investment management, ensuring that an investment portfolio remains aligned with an investor's objectives over time. Due to changes in the economic environment and company policies, the fundamental situation of companies evolves. This paper presents a multi-objective model for portfolio rebalancing based on the Constant Proportion Portfolio Insurance (CPPI) strategy, with the objectives of minimizing risk, minimizing transaction costs, and maximizing the portfolio’s fundamental criteria. The model incorporates interval uncertainty in parameters such as the price-to-earnings ratio and is reformulated using a robust optimization approach. A revised multi-choice goal programming method is applied to solve the model. The proposed method is evaluated in both bullish and bearish market cycles, as well as during a financial crisis, to ensure its robustness and performance across varying market conditions. The results show that, without rebalancing, the investor incurs greater losses during bearish markets. However, by implementing the proposed rebalancing strategy, the portfolio’s floor value is maintained, and the portfolio experiences only a slight decrease in value during market downturns. Additionally, by incorporating fundamental factors, the strategy leads to higher returns and lower risk in bullish markets compared to other strategies.
... TOPSIS complements this by ranking alternatives based on their proximity to a Positive Ideal Solution (PIS) and their distance from a Negative Ideal Solution (NIS) (Hwang and Yoon, 1981). This ranking mechanism operationalizes the concept of relative advantage by quantitatively capturing practitioners' evaluations of key factors, such as cost-effectiveness, energy efficiency, and compliance with regulations. ...
... , n n ). [50]. The TOPSIS method has been applied in a variety of sectors, and its primary advantage is that it can provide both the positive (best) ideal solution and the negative (worst) ideal solution simultaneously. ...
Health tourism is an increasingly vital sector for both Kayseri and Türkiye, contributing significantly to exports and foreign currency inflows. Recent investments in health tourism infrastructure have positioned Kayseri as one of the leading cities in the country, particularly due to its strong healthcare facilities. This study explores Kayseri’s potential in health tourism, with a focus on bariatric surgery, by employing Multi-Criteria Decision Making (MCDM) and optimization methods. The study first provides an extensive literature review to identify the key factors influencing patients’ selection of health institutions for bariatric surgery. Subsequently, the Group Best-Worst Method (G-BWM) is applied using expert input from managers of bariatric surgery centers to determine the relative importance of these factors. Based on the G-BWM findings, nine health institutions in Kayseri offering obesity surgery services are evaluated and ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), which generates institutional performance scores. Building on these results, a Goal Programming model is developed to assign patients to suitable health institutions while simultaneously considering the health institution’s revenue and patient satisfaction. This study offers several novel contributions. It integrates MCDM techniques with goal programming in the context of health tourism—a combination not widely explored in the literature. Additionally, it provides a comparative assessment of the factors influencing health tourists’ decision-making processes, offering policymakers a strategic framework for resource allocation. Lastly, by presenting a mathematical model for patient-institution assignment, the study offers practical guidance for health tourism organizations aiming to enhance both health institution revenue and patient satisfaction in the health tourism sector.
... Given the multi-dimensionality of transport operations, MCDM techniques have gained popularity in performance assessment. Traditional methods such as TOPSIS (Hwang & Yoon, 1981), AHP (Saaty, 1980), and DEA have been applied to rank transport units based on efficiency, productivity, and sustainability indicators. ...
The performance evaluation of State Road Transport Organizations (SRTUs) is essential for ensuring the effective delivery of public transportation services. This study presents a novel multi-criteria decision-making (MCDM) framework employing three geometric similarity-based ranking methods-Ranking by Alternatives Median Similarity (RAMS), Ranking the Alternatives using the Trace to Median Index (RATMI), and Ranking by Alternatives Perimeter Similarity (RAPS). The evaluation is structured around three key dimensions: Physical, Operational, and financial performance. Each dimension comprises a set of relevant indicators to capture the comprehensive functionality of SRTUs. By integrating these advanced ranking techniques, the study facilitates comparison of transport units, enabling more informed managerial decisions. The proposed methodology not only highlights the relative efficiency of different organizations but also provides insights into specific areas of improvement. The results demonstrate the robustness and discriminatory power of the geometric similarity-based methods in prioritizing and benchmarking public transport performance. The results of the geometric similarity based MCDM methods are compared with Multi Attributive Ideal-Real Comparative Analysis (MAIRCA) method
... The criteria were selected based on previous knowledges on stressor impacts to reflect the cumulative effect of dams on the colonization of upstream areas (Kreutzenberger et al. 2020;Lagarde et al., 2021a,b) or to assess diffuse sources of stress caused by urban and agricultural surfaces (Chen and Olden, 2020;Walter et al. 2012). Then, the criteria were combined to obtain a synthetic pressure score for each category by performing a TOPSIS multicriteria decision analysis (Technique for Order of Preference by Similarity to Ideal Solution; Hwang and Yoon, 1981). Briefly, this method is based on a scoring process, bounded between 0 and 1, of a series of alternatives according to their relative distance from extreme favourable and unfavourable conditions, reflected by the maximum or minimum values of criteria. ...
Understanding how tropical rivers change in response to human-induced disturbances represents a major challenge for management and conservation. However, monitoring networks based on ecological indicators remain scarce in oceanic islands, where freshwater indigenous fish and macro-crustacean assemblages are dominated by diadromous species. We investigated the relevance of these taxa for assessing the ecological status of rivers in two tropical islands, Reunion and Mayotte, Indian Ocean, to fulfill objectives of the European Water Framework Directive in overseas regions. Beyond providing insights on ecological responses of fish and macro-crustacean assemblages, we proposed a methodological framework to designed stressors-specific multimetric index by selecting primarily shared metrics between and within islands to improve the robustness and interpretation of this index. Numerous candidate metrics were tested to reflect the alterations induced by three stressors categories (i.e., continuity alteration, agricultural and urbanisation stresses) on the diversity, abundance, or size-structure of assemblages. Our results demonstrated that fish and macro-crustacean assemblages were sensitive to multiple stressors, but the ecological responses were more congruent when facing continuity alterations, compared to land use changes associated with agriculture or urbanization. These migratory species are understandably vulnerable to river fragmentation, but their oceanic dispersive stage favor exchanges between watersheds, which in turn can promote the resilience and persistence of local populations in degraded areas. In such insular context, we thus suggested using fish and macro-crustaceans to firstly assess the state of ecological continuity, whereas other taxa, such as diatom or macroinvertebrates, can be complementary to reflect the alteration of water quality.
... An important model for multicriteria analysis is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. It is a ranking method proposed by Hwang and Yoon (1981) for solving multicriteria decision problems (Srđević, 2002). Random Forest Clustering (RFC) method is a machine learning method that uses a large number of nonlinear algorithms and a statistical learning method designed for classification, regression, and other tasks solved by constructing multiple decision trees and finding a class (classification) or a median/average prediction (regression) of the individual trees (Ho, 1995;1998). ...
Faced with a very picky market and strong competition from high-qulity imported wines, it is necessary to shed light on the terroir characteristics of local wine-growing areas and the typicality of local wines, as this represents an opportunity to enhance the wine sector through geographical indications and the protection of small appellations. A necessary step in this complex process is the application of advanced technologies, i.e. new techniques and different modelling methods, accompanied by a spatial analysis of different parameters through the geographic information system (GIS). This paper presents several examples of application of advanced technologies and development of innovative modelling methods in viticulture and winemaking in the Oplenac wine-growing district (Serbia), all of which have the potential for wider application and adaptation of developed methods to conditions in other wine-growing areas of the region. With the aim of studying the terroir factors, this paper presents modelling performed by applying the Analytical Hierarchy Process (AHP) method, which was used for modelling and classification of the studied abiotic terroir factors in hierarchical levels. The modelling and classification of the abiotic terroir factors in hierarchical levels was performed using the Geographical Detector Method (GDM). Modelling with TOPSIS method was used in this work to present an example of modelling and ranking of analysed anthropogenic terroir factors. The application of the GIS technology was used in this paper to present examples of mapping favorability classes of abiotic and anthropogenic terroir factors and small appellations in particular absolute, elite, historic and organic vineyards, i.e. viticultural parcels. The Random Forest Clustering (RFC) method was used to present examples of wine quality and typicality prediction. Through this modelling, a link is established between the terroir factors studied and wine quality and typicity, which forms the basis for the protection of geographical indications in the EU PDO/PGI system. Finally, a comprehensive classification of viticultural micro-areas was made based on all the viticultural-oenological models developed.
... Falsafi et al. [23] adopt the AHP approach for its ability to handle qualitative criteria, such as training needs and readiness of various technologies; they nevertheless find out that economic sustainability is the criterion with the strongest impact on the regional structure of closed loop slag recycling chain, followed by carbon emissions. The AHP process in combination with TOPSIS (Hwang and Yoon [34]) and fuzzy logic was also used by Mahjouri et al. [35] to select the optimal technology for iron and steel wastewater treatment. Their main criteria are reliability including shutdown problems, system efficiency in pollution removal, sustainability including optimal resource utilization and reuse. ...
... TOPSIS is a widely used MCDM method that was introduced by Hwang and Yoon in 1981 [9]. TOPSIS finds the best solution from a finite set of possible option alternatives by comparing the distance of each alternative to an ideal solution (the best case) and an anti-ideal solution (the worst case). ...
The growing number of educational technologies presents possibilities and challenges for personalized instruction. This paper presents a learner-centered decision support system for selecting adaptive instructional strategies, that embeds the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in a real-time learning environment. The system uses multi-dimensional learner performance data, such as error rate, time-on-task, mastery level, and motivation, to dynamically analyze and recommend the best pedagogical intervention from a pool of strategies, which includes hints, code examples, reflection prompts, and targeted scaffolding. In developing the system, we chose to employ it in a one-off postgraduate Java programming course, as this represents a defined cognitive load structure and samples a spectrum of learners. A robust evaluation was conducted with 100 students and an adaptive system compared to a static/no adaptive control condition. The adaptive system with TOPSIS yielded statistically higher learning outcomes (normalized gain g = 0.49), behavioral engagement (28.3% increase in tasks attempted), and learner satisfaction. A total of 85.3% of the expert evaluators agreed with the system decisions compared to the lecturer’s preferred teaching response towards the prescribed problems and behaviors. In comparison to a rule-based approach, it was clear that the TOPSIS framework provided a more granular and effective adaptation. The findings validate the use of multi-criteria decision-making for real-time instructional support and underscore the transparency, flexibility, and educational potential of the proposed system across broader learning domains.
... 2.6 TOPSIS method TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is a MCDM method developed by Yoon (1980) and Hwang and Yoon (1981) and used for ranking alternatives. The TOPSIS method uses Euclidean distance to rank the alternatives. ...
Purpose
There is a lack of research in the literature evaluating the research performance of countries in the field of education. In addition, research performance is often analyzed using traditional methods. In this study, the research performance of countries in the field of education was analyzed with multi-criteria decision-making methods.
Design/methodology/approach
The research performance of 93 countries was examined with the data of the last 10 years from InCites Benchmarking and Analytics using productivity and impact indicators. In the research, CRITIC, MEREC and Entropy methods, which are among the multi-criteria decision-making (MCDM) methods, were used to weight the performance criteria objectively. Three different criteria weights were analyzed separately by ARAS, MABAC and TOPSIS methods. The different ranking values obtained were combined using the Borda function, and the final values were obtained. Research performance was analyzed using raw, population-normalized and gross domestic product (GDP) data.
Findings
The most important productivity indicator is the number of publications in the top 1%, while the most important publication impact indicator is “Impact Relative to World.” The USA, UK and Australia have the highest research performance in the analysis with raw data, and Macau, Australia and Hong Kong in the analysis are normalized to the population. In the analysis normalized to GDP, Greek Administration of Southern Cyprus, Hong Kong and Australia perform the best. The findings justify the use of more than one MCDM method to weight the criteria and rank the countries.
Originality/value
This study also revealed how MCDM methods can be used to measure research performance.
... Hwang ve Yoon [57] tarafından tanıtılan TOPSIS yöntemi, alternatiflerden maksimum kazancı ya da minimum maliyeti sağlamak için pozitif ideal çözüme en kısa mesafeyi sağlarken, negatif ideal çözüme olan en uzun mesafeyi seçmeyi amaçlamaktadır [58]. Ancak TOPSIS yöntemi, gerçek dünya uygulamalarında eksik ve yanlış bilgilerden dolayı kriterleri ve alternatifleri en kısa ve en uzun mesafeler açısından değerlendiremeyebilir. ...
Dijital pazarlama, klasik pazarlamaya kıyasla daha etkili pazarlama stratejileri oluşturmayı ve hızlı karar almayı sağlar. Pazarlama faaliyetlerinde, hedef kitleler ve kişiselleştirilmiş etkinlikler, daha etkili pazarlama yöntemleri olarak görülmektedir. Dijital pazarlama, bu etkin yöntemi sağlama yeteneğine sahiptir. Bu çalışmada, dijital pazarlamanın değerlendirilmesi için belirlenen kriterlerin önemi, alfa seviyesine dayalı bulanık entropi yöntemi kullanılarak elde edilmiştir. Bu sonuç, Pisagor bulanık TOPSIS ve bulanık TOPSIS yöntemlerinde kullanılmıştır. Pisagor bulanık TOPSIS ve bulanık TOPSIS yöntemleri, üretim tesislerinde aynı değerlendirme kriterleri ile karşılaştırılmıştır. Sonuç olarak, web sitesi etkinliği, e-posta pazarlaması ve dijital pazarlama için kullanılan bilgi teknolojisi uygulamaları en önemli değerlendirme kriterleri olarak belirlenmiştir. Bu kriterler kullanılarak şirketlerin dijital pazarlama yetkinlikleri sıralanmış ve işletmeler arası bir değerlendirme sistematiği oluşturulmuştur.
... The CoCoSo model, based on an integrated SAW and exponentially weighted product model, was proposed by [43] and utilizes Max-Min normalization. The TOPSIS method, based on the principle that alternatives have the shortest distance to the positive ideal solution and the longest distance to the negative ideal solution, was developed by [44] and employs vector normalization. The WASPAS method, developed by [45], employs additive normalization. ...
This study assesses the progress of EU countries in achieving the Sustainable Development Goals (SDGs) using Multi-Criteria Decision-Making (MCDM) methods. The evaluation covers 27 countries and is based on 15 indicators for the 2019–2021 period. The MPSI-RAPS model was employed to determine indicator weights and rank the alternatives. To ensure robustness, a comprehensive sensitivity analysis was conducted across 16 scenarios. The final rankings from the MPSI-RAPS model identified Sweden, the Netherlands, and Germany as the top-performing countries in sustainable development progress. Notably, rankings varied significantly across scenarios, underscoring the impact of methodological choices on outcomes.
... The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is one of the first methods in the field of multi-criteria decision-making (MCDM). Formulated by Hwang and Yoon [18], TOPSIS relies on the idea that the most desirable alternative ought to be the closest to the positiveideal solution (PIS), which concentrates on benefit maximization and cost minimization, and the farthest from the negative-ideal solution (NIS), where costs are maximized and benefits minimized. Traditionally, TOPSIS assumes that decision-makers possess precise information about both the criteria weights and performance ratings. ...
Determining warehouse locations is one of the most critical and strategic decisions in logistics systems and supply chains. In most cases, the process of warehouse location selection is posed as a multi-criteria decision-making (MCDM) problem where planners must choose the best site among several alternatives based on a set of qualitative and/or quantitative criteria. The aim of this study is to perform a comparative analysis of two well-known fuzzy MCDM methods, the Fuzzy Technique for Order Preference by Similarity to an Ideal Solution (FTOPSIS), the Fuzzy Analytic Hierarchy Process (FAHP), along with a hybrid approach that combines both methods to determine the most suitable warehouse location. Our analysis mainly focuses on evaluating the applicability of these methods in selecting the optimal warehouse location, using a case study of Entekhab Industrial Group, one of the largest home appliance manufacturers in Iran.
... The scoring process aims to solve the multi-criteria decision-making problem, enables a comprehensive evaluation of all potential candidates by integrating multiple factors. TOPSIS (Hwang and Yoon 1981) is a method widely used in various fields, such as logistics, engineering and manufacturing, business and marketing management, energy, and chemistry, for dealing with multi-criteria decision-making problems. Among many algorithms designed to solve the multicriteria decision-making problem, TOPSIS is relatively robust (Zanakis et al. 1998). ...
Countries are now shifting from one-off lunar exploration missions to the establishment of a lunar base for long-term sustainable surveys. The selection of a suitable site plays a crucial role in sustaining the base’s operation and facilitating scientific research. Previous site selection methods have been limited in their ability to consider multiple objectives and factors simultaneously, often relying heavily on expert knowledge. To address this challenge, this paper proposes a comprehensive site selection method that integrates multiple engineering and scientific objectives/factors. Through site selection factor comprehending, gridded data processing and site evaluation based on Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the proposed method balances subjective and objective considerations and outputs quantitative descriptions of the most suitable candidate sites. This paper applies the proposed method to the range of 75°S − 90°S. The results reveal four large areas with continuous high suitability near the South Pole, while a small area located at the rim of Cabeus B crater shows the highest suitability. Qualitative and quantitative comparisons are conducted between the areas selected by the proposed method, areas recommended by previous studies, and areas announced by Artemis III. The candidate areas identified in this paper outperform others in terms of a wider range of site selection factors, making them valuable references for future lunar base site determination. Additionally, the proposed site selection method holds relevance for similar site selection tasks where multiple objectives are set. It offers a more automated and quantifiable approach, minimizing manual intervention and providing robust results for decision-making processes.
... The multiple criteria selection methodology used was TOPSIS [52][53][54]. The outcome of the TOPSIS model, which uses the [55] extension for group decision-making, is an effectiveness index that ranks agricultural practices by their perceived effectiveness. ...
This study assesses local stakeholders’ perceptions regarding how a Mediterranean cereal-based cropping system could transition to a more sustainable production, focusing on the identification of the most suitable alternatives for their diversification. Fifty-four stakeholders from the Aragon region in Spain, including farmers, technical advisors, public agricultural officers, local researchers, and experts from environmental NGOs, were consulted. Their responses were analysed using multi-criteria decision-making techniques to order their preferences for different farming practices and diversification strategies. Stakeholders’ responses suggest a priority for balancing soil conservation with the economic viability and continuity of farms. This is evident not only in its consideration as a priority objective but also in their preferences for farming practices, where their implications for farm profitability, especially through the choice of less costly alternatives, are a main concern. This economic rationale also influences their choice of crop diversification alternatives, with a preference for short (two-year) rotations in rainfed cereals and double cropping in irrigated cereals, showing a consideration of the balance between environmental and economic sustainability, and for diversification crops that farmers are already familiar with, aiming both to reduce the uncertainties linked to new crops and to minimise the need for technical support.
... TOPSIS was developed by Hwang and Yoon in 1981 [61] and was later presented by Chen and Hwang in 1992 [62]. This decision-making method is extended to evaluate multiple criteria to identify a balanced solution [63]. ...
Railway networks are highly susceptible to land subsidence, which can undermine their functional stability and safety, resulting in recurring failures and vulnerabilities. This paper aims to evaluate the susceptibility of the railway network due to Qanat underground channels in the city of Bafq, Iran. The criteria considered for assessing the susceptibility of Qanats subsidence on the railway network in this study are Qanat channel density, Qanat well density, discharge rate of the Qanat, depth of the Qanat, railway traffic, and the railway passing load. The subjective determination of criteria weights in Multi-Criteria Decision-Making (MCDM) for susceptibility analysis is typically a complex, time-consuming, and biased task. Furthermore, there is no comprehensive study on the impact and relative significance of Qanat-related factors on railway subsidence in Iran. To address this gap, this study developed a novel spatial objective weighting approach based on Principal Component Analysis (PCA)—as an unsupervised Machine Learning (ML) technique—within a spatial decision-making framework specifically designed for railway susceptibility assessment. In the proposed framework, the final Qanat-induced subsidence susceptibility zoning was conducted using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. This study identified 7.7 km² of the total area as a high-susceptibility zone, which encompasses 15 km of railway network requiring urgent attention. The developed framework demonstrated promising performance without deploying subjective information, providing a robust data-driven approach for susceptibility assessment in the study area.
... Despite their heterogeneity, they all expose the possibility of predicting behavior to predict actions by combining criteria of different natures and requires a series of steps in which decisions must be made. [25][26][27]. This enables preparation and response programs to reduce the negative impacts of these natural disasters. ...
The occurrence of earthquakes may have catastrophic and devastating consequences for the inhabitants of the place where they occur. Some regions are characterized by the high frequency of this type of natural phenomenon. Such is the case of Ecuador, a country with a high seismic index due to its location in a subduction zone between the Pacific Plate and the South American Plate. Predictions in the behavior of earthquakes are a way of prevention that allows taking measures according to vulnerability. Although it is difficult to accurately predict the occurrence of an earthquake, there are dissimilar types of analysis to observe its behavior and patterns of occurrence. The nature of earthquakes and their monitoring variables usually make up large databases. For its processing and subsequent analysis of the results, it is convenient to use statistical techniques of Data Mining such as K-Means. In this work, the classic K-Means method is combined with Neutrosophy to improve the results obtained by taking into account the indeterminacy of such complex data sets and including the diversity of the data and its fluctuation, due to the proximity among the boundaries and their membership clusters.
... Keunggulan dari MCDA terletak pada kemampuannya untuk menyajikan informasi yang komprehensif dan transparan, yang memungkinkan para pihak dalam negosiasi untuk memahami trade-offs antara berbagai kriteria. Dalam banyak kasus, penggunaan MCDA dapat mengurangi ketidakpastian dan meningkatkan kepuasan dari semua pihak yang terlibat, karena keputusan yang diambil didasarkan pada analisis yang mendalam dan mempertimbangkan sudut pandang yang beragam (Hwang & Yoon, 1981). 4. Teknik "ZOPA" (Zone of Possible Agreement) Teknik Zone of Possible Agreement (ZOPA) berfokus pada identifikasi area di mana kesepakatan dapat dicapai berdasarkan kepentingan dan posisi kedua belah pihak. ...
The analysis of the processes that lead to choices and the elements that condition them converges in decision theory Keeney and Raiffa (1993). In most cases, the theories that deal with decisions presuppose the perfect rationality of the decision-maker and therefore, the ability to identify the best choice through an essentially analytical process that can always be traced back to logical structures. In this sense, for years the theory par excellence was the theory of expected utility Von Neumann and Morgenstern (1947). In reality, however, perfect rationality does not always represent a model capable of interpreting the processes of choice Tversky and Kahneman (1974). In fact, empirical studies have shown that decision-makers implement a series of heuristics in making a choice, which causes the violation of the axioms of rationality. Re-proposing a famous Kahneman and Tversky empirical experiment based on prospects Tversky and Kahneman (1989), this work aims to study the preferences of decision-makers by relating the behavioural anomalies found and multi-criteria methods. On the obtained outputs, we test three different multi-criteria methods – ELECTRE III, PROMETHEE and TOPSIS – to determine whether they are able to explain the behaviour of the decision-makers. The results of our study show that the TOPSIS method provides a ranking that reflects the preferences expressed by the majority of individuals.
The global imperative to address climate change and resource depletion requires innovative and sustainable strategies in the construction sector. This paper explores a methodological approach for integrating Circular Economy (CE) principles into the regeneration of the built environment. It places particular emphasis on adopting a comprehensive, transcalar perspective to ensure effective implementation. Redefining the traditional linear model of construction, the adoption of CE in building regeneration seeks to minimize waste, optimize resource use, and promote long-term resilience, in line with EU directives promoting sustainability and circularity in the built environment.
The presentation will explore the key aspects of a circular design approach, including an application case study that examines the regeneration and adaptive reuse of a craft/residential neighborhood in Prato. Through a comprehensive analysis of existing literature, a series of circular design principles were identified. Circular strategies are declined according to the different scales of design: from urban environments to building-scale choices and construction materials and techniques, providing insights into indicators for assessing circularity.
Different regeneration scenarios are assumed and compared according to a multi-criteria approach, based on circular design principles, in order to achieve sustainable regeneration results and highlight the benefits of adopting circular strategies at different project scales.
The analysis framework considers the entire life cycle of the regeneration process, from design and construction to operation and end-of-life. The integration of a simplified Life Cycle Assessment (LCA) will provide a systematic evaluation of the environmental impacts associated with the entire life cycle of a building. LCA will be employed to assess the environmental implications of various building materials, construction processes, and end-of-life scenarios, guiding decision-makers in making informed choices that align with circular and sustainable principles.
In conclusion, this presentation aims to explore an approach toward the circular transition in built environment regeneration. By adopting a global and multilevel perspective, we can actively contribute to a future that is environmentally sustainable and resilient and that meets the need, also addressed by the European Union, to move from a linear to a circular development model.
Multiple attribute decision making (MADM) selects the optimal alternative(s) or sorts alternatives from best to worst based on evaluation information of multiple attributes and provides an effective solution for complex multi-dimensional decision-making problems in the field of economics, management, engineering and many others. Based on classical MADM approaches, extensive linguistic MADM models were proposed especially the distributed linguistic MADM methods, which have become an effective tool for the representation of attribute preferences.
In this study, analysis of a multi-response experimental data set was considered. The multi-response experimental data set, which have linearly correlated responses, was analyzed in three stage. In the first stage, called modeling, the multi-response experimental data set was modeled by using Seemingly Unrelated Regression (SUR) due to linear relationship between the responses. The second stage, called multi-objective optimization, was achieved by using multi-objective metaheuristic methods, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Multi Objective Differential Evolution (MODE). In the last stage, called decision making, the obtained results were discussed and compromise experimental conditions were determined by using Multi-Criteria Decision Making (MCDM) methods, called TOPSIS, MABAC, CODAS. It is seen from the results that parameter estimates of the SUR method has more reliable than the ordinary least square (OLS) estimates. Pareto solution set of the MODE is more prefable according to the performance metrics and the TOPSIS and the CODAS give same compromise solution among the Pareto solutions. The obtained compromise solution can be used as an experiment condition by the researcher confidently.
This paper presents an integrated approach to aggregate production planning (APP) that combines possibilistic linear programming
(PLP) with the throughput accounting system for profit maximization. APP involves making strategic decisions on production
levels, inventory management, and resource allocation to meet customer demand while minimizing costs and maximizing
profitability. However, the inherent uncertainties and complexities of real-world production environments pose significant
challenges to traditional planning models. To address these challenges, this paper proposes the integration of PLP with fuzzy goal
programing and the throughput accounting system at the very end, using data received from Rich Pharmaceuticals Ltd, the study's
findings were derived using Lingo version 18 software (RPL). The model incorporates possibility distributions of input parameters,
allowing decision-makers to consider the uncertainties and imprecisions in demand forecasts, production costs, and capacity
constraints. By maximizing profit while considering risk tolerance, it also enables more realistic and reliable production planning
decisions
Key Words: Aggregate production planning, fuzzy demands, capacity utilization, Decision maker, throughput accounting
Soil erosion is a significant environmental issue in the Himalayan region, driven by steep terrain, dynamic climatic conditions, and increasing anthropogenic pressures. This study assesses soil erosion susceptibility in the Bhagirathi River Basin, Indian Himalaya, by integrating geospatial techniques with multi-criteria decision analysis (MCDA). The erosion susceptibility assessment is performed at the sub-watershed level with selected suitable morphometric parameters. The Analytical Hierarchy Process (AHP) assigned weights to these parameters based on expert judgment, while the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) ranked 100 sub-watersheds according to erosion susceptibility. Results reveal that over 35% of the basin area faces a moderate to high risk of soil erosion and sediment deposition, with several sub-watersheds identified as high-priority zones requiring immediate intervention. The integrated AHP–TOPSIS approach demonstrates a robust, GIS-based framework for sub-watershed prioritization, offering clear, quantitative guidance for sustainable watershed management, soil conservation, and sediment control strategies. Additionally, the study aligns with key Sustainable Development Goals (SDGs): SDG 2 (sustainable food production), SDG 3 (soil protection for health and well-being), SDG 13 (climate action), and SDG 15 (land restoration). By linking erosion susceptibility mapping with global sustainability targets, the findings contribute to climate-resilient catchment management and effective land restoration in fragile mountain ecosystems. This research underscores the transformative potential of geospatial innovations for informed decision-making and sustainable water resource management in complex riverine and catchment systems.
This study examined branched-chain fatty acids (BCFAs)’ effects on oxidative stress, energy metabolism, inflammation, tight junction disruption, apoptosis, and Toll-like receptor 4/nuclear factor kappa-B (TLR4/NF-κB) signaling in lipopolysaccharide (LPS)-induced calf small intestinal epithelial cells (CSIECs). Eight groups were used: a control group, an LPS-induced group, and six BCFA treatment groups (12-methyltridecanoic acid (iso-C14:0), 13-methyltetradecanoic acid (iso-C15:0), 14-methylpentadecanoic acid (iso-C16:0), 15-methylhexadecanoic acid (iso-C17:0), 12-methyltetradecanoic acid (anteiso-C15:0), and 14-methylhexadecanoic acid (anteiso-C17:0)) with LPS. The BCFA pretreatments significantly increased CSIEC activity compared to the LPS-induced group, with iso-C14:0 showing the highest activity (89.73%). BCFA reduced Reactive Oxygen Species (ROS) generation and malondialdehyde (MDA) levels and improved the superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) activities and glutathione (GSH) levels. Iso-C16:0 optimized total antioxidant capacity (T-AOC). BCFA enhanced the mitochondrial membrane potential, Adenosine Triphosphate (ATP) enzyme activity, and ATP content, with iso-C14:0 increasing ATP by 27.01%. BCFA downregulated interleukin (IL)-1β, IL-8, tumor necrosis factor (TNF)-α, and interferon (INF)-γ gene expression, reduced IL-6 levels, and increased IL-10 expression. Myeloid differentiation factor 88 (MyD88) mRNA levels were reduced. BCFA alleviated Zonula Occludin (ZO-1), Claudin-1, and Claudin-4 decrease and increased Occludin levels. BCFA mitigated LPS-induced increases in Caspase-3 and BCL2-Associated X (BAX) mRNA levels, reduced Caspase-8 and Caspase-9 expression, and increased B-Cell Lymphoma-2 (BCL-2) mRNA levels. The Entropy Weight-TOPSIS method was adopted, and it was discovered that iso-C15:0 has the best effect. In summary, BCFA supplementation mitigated oxidative stress and enhanced mitochondrial function. BCFA inhibited TLR4/NF-κB signaling pathway overactivation, regulated inflammatory cytokine gene expression, reduced cellular apoptosis, preserved tight junction integrity, and supported barrier function.
This study addresses the challenge of effectively modeling uncertainty and hesitation in complex decision-making environments, where traditional fuzzy and vague set models often fall short. To overcome these limitations, we propose the Fermatean neutrosophic vague soft set (FNVSS), an advanced extension that integrates the concepts of neutrosophic sets with Fermatean membership functions into the framework of vague sets. The FNVSS model enhances the representation of truth, indeterminacy, and falsity degrees, providing greater flexibility and resilience in capturing ambiguous and imprecise information. We systematically develop new operations for the FNVSS, including union, intersection, complementation, the Fermatean neutrosophic vague normalized weighted average (FNVNWA) operator, the generalized Fermatean neutrosophic vague normalized weighted average (GFNVNWA) operator, and an adapted Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. To demonstrate the practicality of the proposed methodology, we apply it to a solar panel selection problem, where managing uncertainty is crucial. Comparative results indicate that the FNVSS significantly outperforms traditional fuzzy and vague set approaches, leading to more reliable and accurate decision outcomes. This work contributes to the advancement of predictive decision-making systems, particularly in fields requiring high precision, adaptability, and robust uncertainty modeling.
Financial inclusion concerns are among the top socioeconomic issues on the agendas of governments, central banks, financial institutions, international organizations and politicians. Interest in these issues is rapidly expanding. To own a bank account does not guarantee use of financial services and it’s not the only measure of financial inclusion. There are several parameters that capture how inclusive a financial system is. A multi-dimensional financial inclusion index (FII) is suggested in this study to measure financial inclusion in India pre and post COVID-19 to check how resilient the Indian economy is. Eight financial inclusion parameters were used in the index's calculation. This research uses equal weights to compute the FII for the years 2019–20 and 2023–24. The results indicate that over the course of the study, there has been a 0.008 point increase in value for India on FII. India has a score of 0.111 and 0.119 for the financial years 2019–20 and 2023–24 respectively, which places it in the category of “low level of financial inclusion.” The findings show that even if a number of government initiatives have made significant progress, much more work must be done to get the economy to a level of full financial inclusion.
This paper presents a unique multi-Q valued bipolar picture fuzzy set (MQVBPFS) methodology to tackle issues in cybersecurity risk assessment under conditions of ambiguity and contradicting data. The MQVBPFS framework enhances classical fuzzy theory through three key innovations: (1) multi-granular Q-valued membership, (2) integrated bipolarity for representing conflicting evidence, and (3) refined algebraic operations, encompassing union, intersection, and complement. Contemporary fuzzy set methodologies, such as intuitionistic and image fuzzy sets, inadequately encapsulate positive, negative, and neutral membership degrees while maintaining bipolar information. Conversely, our MQVBPFS architecture effectively resolves this restriction. Utilizing this framework for threat assessment and risk ranking, we create a tailored cybersecurity algorithm that exhibits 91.7% accuracy (in contrast to 78.2–83.5% for baseline methods) and attains 94.6% contradiction tolerance in empirical evaluations, alongside an 18% decrease in false negatives relative to conventional approaches. This study offers theoretical progress in fuzzy set algebra and practical enhancements in security analytics, improving the handling of ambiguous and conflicting threat data while facilitating new research avenues in uncertainty-aware cybersecurity systems.
Celem badania była ocena zróżnicowania poziomu rozwoju społeczno-gospodarczego w małych państwach wyspiarskich Globalnego Południa (SIDS). Badaniu poddano 38 państw w dwóch latach, w 2019 r. i 2022 r. Państwa te zostały pogrupowane wg stworzonych na potrzeby analizy trzech modeli rozwojowych: model pomocowo-przekazowy (MPP); model rolniczo-przemysłowy (MRP) oraz model usługowy (MU). Metoda. Do oceny rozwoju społeczno-gospodarczego SIDS zastosowano metodę porządkowania liniowego TOPSIS. Konstrukcji miernika syntetycznego dokonano na zbiorze 15 cech diagnostycznych. Zastosowana metoda TOPSIS jest pierwszą w polskiej literaturze przedmiotu próbą wyznaczenia zróżnicowania poziomu rozwoju w przypadku małych państw wyspiarskich Globalnego Południa. Wyniki. Pomimo wystąpienia istotnych wydarzeń w gospodarce światowej między latami poddanymi analizie, w tym pandemii COVID-19, nie zauważono diametralnych różnic w kolejności stopnia rozwoju społeczno-gospodarczego w analizowanych SIDS.
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