Adiel Teixeira de Almeida’s research while affiliated with Federal University of Pernambuco and other places

Accepted by: Konstantinos Nikolopoulos The paper presents a real-world decision-making problem in the context of the Brazilian Federal Police (BFP), which consists of establishing priorities for police operations. This study deals with allocating resources to trigger police operations that, while demanding more resources and specialized techniques, also promote the effectiveness of police actions more conspicuously and directly. Driven by the value-focused thinking methodology, the objectives and values of the Federal Police were structured and represented by criteria, which let police operations be evaluated and prioritized. The Flexible and Interactive Tradeoff method was applied to rank the operations, with an innovative methodological perspective, which integrates two different paradigms for preference modelling: elicitation by decomposition and holistic evaluations. A mathematical modelling approach is presented to deal with the combination of both types of information obtained by the decision-maker (DM), in order to search for dominance relations between alternatives. This study shows how incorporating holistic judgements in the process can be useful for tightening the decision process since the inequalities obtained with holistic judgements have a high impact on the space of weights compatible with the DM’s preferences. A clear conceptual framework is presented for the analysis, showing how the application of such a combined approach to prioritizing special police operations adds a step to the decision-making processes and policies of the BFP, thereby broadening the managerial implications of tackling public security issues by seeking to solve them using management mathematics.

Aggregate Production Planning (APP) aims at balancing the forecast demand for product families with the available production resources, thus allowing changes to be made in the system and the best action strategy to be found. APP decisions are strategic decisions for the organization, which take an intermediate time horizon which spans 12 months, in general. As different issues may influence business success, this kind of decision problem will take multiple objectives into account, when a strategic view is considered. Conflicts between objectives frequently increase the complexity of APP problems. In order to deal with this kind of problem, this paper proposes a multi-criteria decision model considering the five objectives related to manufacturing strategy, namely: quality, speed, dependability, flexibility, and cost. By applying a multi-objective optimizing model which considers the organization’s strategical objectives, and by using the NSGA-II algorithm, a subset of representative solutions of the Pareto Frontier is obtained, thereby enabling the application of the FITradeoff method. A multi-criteria method, such as the FITradeoff, assists Decision Makers (DMs) in choosing a production plan more suitable to their objectives. The results show that the FITradeoff method contributes to the evaluation of solutions by aiding the DM to consider a significant set of alternatives while at the same time reducing the cognitive effort that he/she needs to make. Keywords: aggregate production planning; manufacturing strategy; FITradeoff method; Multi-Criteria Decision-Making (MCDM); NSGA-II

In an uncertain world, decision support systems (DSSs) are essential for effective portfolio management. Electricity companies often face challenges in allocating limited resources among competing projects, influenced by sustainability and regulatory requirements. To address these challenges, multicriteria approaches have been developed, focusing on complex issues involving outranking methods. This paper introduces a methodological advance with a novel algorithm that enhances the c‐optimal PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) approach, resolving scaling issues inherent in the PROMETHEE V method. Our key contribution is a refined procedure for efficiently identifying and comparing c‐optimal solutions while preserving the method's axiomatic integrity, ensuring the selection of the “true best” portfolio. Additionally, we present a web‐based DSS designed to implement this methodology, featuring interactive visualization and sensitivity analysis tools. Freely available online, both the algorithm and DSS were validated through a case study with a Brazilian electricity company, demonstrating their practical benefits and applicability across various business contexts.

The Flexible and Interactive Tradeoff (FITradeoff) multicriteria method was developed under the scope of the Multiattribute Value Theory (MAVT) to elicit preferences under a partial information perspective. The flexibility of this method has been recently enhanced by the combination of two paradigms of preference modeling in the decision process, namely elicitation by decomposition (ED) and holistic evaluation (HE), improving the preferences elicitation task in a sense that fewer elicitation questions are expected to be answered by the Decision Maker (DM) to find a recommendation for the multicriteria decision making (MCDM) problem. The combination of two preference modelling paradigms in FITradeoff is an innovative characteristic on MCDM methods which deserves further analysis on its implications for the practice of decision making, not yet investigated in previous works. Considering that, this work aims to evaluate the impact of conducting HE in FITradeoff in terms of the expected reduction of the number of questions (NQ) that shall be answered to obtain the problem results. To do so, a simulation study has been carried out, in which multiple criteria problems have been generated and solved by simulating different preferences profiles. Hypotheses on the reduction of the number of questions were formulated and tested for identifying the actual effect of two different types of HE in the elicitation process: selection of the best alternative and elimination of the worst alternative considering a previously defined subset. Besides, we also analyze the relationship between the HE effects and important variables of MCDM problems such as number of criteria (NC), number of alternatives (NA), and weights distribution patterns (WD). The results obtained show that holistic evaluation judgments have a significant impact on the reduction of effort made by the DM in the elicitation process, in a sense that the total number of questions reduces in a significant manner, considering either selection tasks or elimination tasks in HE. Keywords: multicriteria decision making; FITradeoff method; holistic evaluation; simulation

Facility location-related decision problems pose a significant challenge for managers due to the multiple and conflicting factors involved. Moreover, incorrect decisions can lead to substantial impacts on companies' long-term strategic planning, resulting in losses for the business. This paper deals with a facility location problem in the educational sector in the northeast region of Brazil, which concerns the definition of the best location to place a private sector technical school, considering multiple objectives throughout a multicriteria approach. The decision-making process is structured based on a 9-step multicriteria model, and the preference elicitation phase is aided by the Flexible and Interactive Tradeoff (FITradeoff) method, using partial information provided by the decision-maker (DM). In the application presented in this paper, preference modeling is conducted considering the combination of two preference elicitation paradigms in the FITradeoff decision process: elicitation by decomposition and holistic evaluations, throughout a flexible approach. The DM’s preferences are elicited interactively, by means of a Decision Support System (DSS). At each interaction, the information given by the DM acts as constraints for a linear programming problem (LPP) model, which is computed in order to verify the potential optimality of each alternative. At the end of the elicitation process, a sensitivity analysis is performed so as to verify the robustness of the results obtained. Insights on the preference modeling paradigms combination with potential advantages for the decision process are also discussed in this paper. Keywords: facility location; technical school location problem; multicriteria decision-making; preference modeling; FITradeoff method

Combining the traditional elicitation by decomposition with holistic evaluations within a decision process with multiple criteria is a peculiar aspect of the Flexible and Interactive Tradeoff (FITradeoff) method since two paradigms in preference modeling are integrated. Even though this integration leads to significant benefits to the decision process, it brings several implications that deserve a deep and detailed analysis with regard to some analytical aspects of the mathematical modeling of the method. Integrating the information obtained by these two different protocols causes significant modifications in the space of weights that may have noteworthy impacts on the results. Hence, this paper focuses its efforts on tackling and investigating such aspects of the FITradeoff method. We analyze properties and analytical aspects of FITradeoff in depth, in order to investigate how the information of holistic judgments can be inserted into the mathematical model of FITradeoff and to determine the potential implications of such integration, such as defining preference relationships and identifying potentially optimal alternatives. In addition, a new heuristic to reduce the number of questions in the elicitation by decomposition of FITradeoff is proposed. We also address situations of inconsistencies that may arise due to the conflicting information provided by decomposition and holistic judgments, as well as ways to solve such inconsistencies.

Several Decision Support Systems (DSS) have been presented in literature. This paper presents an Information and Decision System that has been performed to implement a Framework for building decision models in the context of Multi-Criteria Decision Making/Aiding (MCDM/A) approach. This system incorporates the steps of the framework in order to support DMs to build decision models. This system does not intend to suggest a specific MCDM/A method but can be used to structure the model with rigor following the framework steps. In addition, this system can be used to document important steps of the process. The DSS also provides flexibility for users since they can return to previous steps to review or adjust some points. Also, the DSS is interactive since the users present preferential information in all steps. An important step presented in the system regards the preference modeling process. During this step, Decision-Makers (DMs) should contextualize the rationality presented in the MCDM/A problem. Moreover, several tests of consistency are done in order to improve the system and to understand how DMs define the rationality of those problems and if they stay consistent with their rationality during the process. In addition, the DSS included several aspects of Problem Structuring Methods, considering important aspects that are not considered in the previous version of the framework. In special, concepts of the Value Focus Thinking method have been included in the system to support the definition of objectives, criteria, and alternatives. This feature improves the new version of the framework. This DSS presents the most important steps of the framework and also provides insights for the development of behavioral studies, which can bring advances in the MCDM/A approach.

The world’s digital transformation changed organizations’ routines completely. Decision Support Systems have been developed to support Decision-Makers to capture information intended to permit competitive advances. In this context, regarding Multi-Criteria Decision-Making/Aiding problems, several DSSs have been proposed to support DMs to deal with complex problems. This paper presents the DSS constructed to implement the FITradeoff method. Several steps of the FITradeoff DSS have been described considering a supplier selection process. In addition, the paper presents behavioral studies performed to investigate the FITradeoff method in a synthesized way. The probability of success, which is an important feature proposed by behavioral studies, has been discussed since it can be used by analysts to advise decision-makers during the decision process. This feature uses previous knowledge of holistic evaluation studies to advise decision-makers to use or not use visualizations to perform holistic evaluations in the FITradeoff Decision Support System. Behavioral studies in the FITradeoff DSS provide modulation (transformations) on it, bringing important advances to this area of knowledge.