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The value of superior supply network design is becoming increasingly important, especially in the perishable supply chain. Due to the recent developments in perishable products, perishable product supply chain (PPSC) management has attracted many researchers. The purpose of this study was to present a multi-period and multi-echelon perishable suppl...
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... Al-Refaie and Kokash [26] addressed a sustainable reverse logistics problem under an uncertain environment with the goal of maximizing profit and positive social impact as well as minimizing CO2 emissions. Meidute-Kavaliauskiene et al. [27] modeled a multiple-period supply chain network under an uncertain environment for perishable products considering customer satisfaction, environmental impacts, costs, and procurement time. Allehashemi et al. [28] considered a closed-loop supply chain network with the goal of minimizing costs, maximizing quality, and minimizing CO2 emissions and solved it with the GAMS software 32.1.0. ...
Supply chain management and distribution network design has a racted the a ention of many researchers in recent years. The timely satisfaction of customer demands leads to reducing costs, improving service levels, and increasing customer satisfaction. For this purpose, in this research , the mathematical programming models for a two-level distribution network including central warehouses, regional warehouses, and customers are designed so that several products with definite demands in multiple periods are distributed from central warehouses to customers. In this problem, two objective functions are considered. The first objective function seeks to minimize the costs of establishment, transportation, inventory, and shortage, and the second objective function a empts to maximize the satisfaction level corresponding with the supply rate of different goods for numerous customers. The presented models include the basic model, inventory-based model, multi-period inventory-based model, and multi-period inventory-based reverse logistics model. The validation and applicability of the proposed models were demonstrated by implementation in a real case study of the automobile industry. The LINGO software 20.0 was used to solve the models. The results show that incorporating the inventory management policies into the basic model and converting from a single-period to a multi-period reverse logistics model will significantly increase company profitability and customer satisfaction.
... Perishable products refer to goods whose quality or quantity gradually decays or deteriorates with time (e.g., pharmaceutical products, dairy products, fruits, vegetables, flowers, and blood products) [1,2]. These products have attracted increasing attention from academics and industries in recent years for their fundamental importance in many industries and trade environments and close relations to human lives [3][4][5]. ...
In today’s perishable products industry, the importance of sustainability as a critical consideration has significantly increased. This study focuses on the design of a sustainable perishable product supply chain network (SPPSCN), considering the factors of economics cost, environmental impacts, and social responsibility. The proposed model is a comprehensive production–location–inventory problem optimization framework that addresses multiple objectives, echelons, products, and periods. To solve this complex problem, we introduce three hybrid metaheuristic algorithms: bat algorithm (BA), shuffled frog leaping algorithm (SFLA), and cuckoo search (CS) algorithm, all hybrid with variable neighbourhood search (VNS). Sensitivity to input parameters is accounted for using the Taguchi method to tune these parameters. Additionally, we evaluate and compare these approaches among themselves and benchmark their results against a reference method, a hybrid genetic algorithm (GA) with VNS. The quality of the Pareto frontier is evaluated by six metrics for test problems. The results highlight the superior performance of the bat algorithm with variable neighbourhood search. Furthermore, a sensitivity analysis is conducted to evaluate the impact of key model parameters on the optimal objectives. It is observed that an increase in demand has a nearly linear effect on the corresponding objectives. Moreover, the impact of extending raw material shelf life and product shelf life on these objectives is limited to a certain range. Beyond a certain threshold, the influence becomes insignificant.
... Much research has also been conducted to find an efficient routing policy for perishable goods. Meidute-Kavaliauskiene et al. (24) addressed a VRP multi-period and multi-echelon perishable supply chain problem concerning procurement time, cycle cost, and customer satisfaction. This study presented a new form accounting for environmental considerations, cost, procurement time, and customer satisfaction, such that the total costs, delivery time, and the emission of pollutants in the network were minimized while customer satisfaction was maximized. ...
Considering the evolution of the food industry and its challenges, like high perishability, managing the food industry supply chain is a key focus for researchers and decision-makers. Uncertainty in decision-making has gained importance, particularly in the yogurt industry, known for its complexity. This study addresses production and distribution planning, scheduling, and routing in the yogurt supply chain. The problem is characterized by multiple products, a single plant, multiple distribution centers, multiple periods, and various transportation methods. A mixed-integer non-linear programming (MINLP) model is used to minimize total costs, including production, setup, overtime, unmet demand, and transportation. Additionally, a robust fuzzy programming approach is applied under uncertainty, with linearization procedures proposed to convert it into a linearized mixed-integer programming formulation. The problem is tested with two data types: a sample problem in three sizes (small, medium, and large) and real data from Kalle Dairy Company, Iran. A Genetic Algorithm (GA) is developed to solve the problem, with necessary modifications made for its application. The GA's performance is compared to an exact algorithm (Branch & Cut), showing that the company's production policy adapts daily to meet demand precisely. The shift to smaller batch production and longer shelf life allows better stock allocation and avoids shortages in uncertain conditions. The company's policies adapt to severe fluctuations in the business environment, though this requires high costs, such as inventory maintenance.
... Kyriakakis et al. [7] proposed a Hybrid Tabu Search -Variable Neighborhood Descent (HTS-VND) metaheuristic algorithm to solve the cumulative capacity restriction vehicle routing problem with time windows. Meidute-Kavaliauskiene et al. [8]presented a multi-period, multi-regional perishable product supply chain considering procurement time, periodic cost, and customer satisfaction, aiming to minimize the total cost, delivery time, and pollutant emissions in the network while maximizing customer satisfaction. In the process of constructing the aforementioned models, the number of objectives and constraints continually increases to more closely approximate real-world descriptions, which adds to the difficulty of solving the problem. ...
This article provides a comprehensive overview of the application of Multi-Criteria Decision Making (MCDM) methods in the field of logistics location selection. It traces the historical development of MCDM methods from their inception in the 1970s to the sophisticated models and algorithms used today, highlighting the evolution from simple models to complex, intelligent algorithms that incorporate environmental and social considerations. The article emphasizes the importance of combining various MCDM methods to leverage their strengths and address their limitations. It showcases the successful application of these hybrid models in diverse scenarios, such as urban transit hub optimization, inland dry port selection, and the positioning of emergency logistics centers. The article concludes by identifying current challenges, such as handling uncertainties and the complexity of models, and suggests future directions for research, including the development of adaptive models and the integration of artificial intelligence and big data analytics to enhance decision-making in logistics location selection.
... In the figure, the demand for fresh bananas tends to be stationary because the demand is already considered to be the same as the needs of the nine basic commodities consumed daily. The fresh fruit supply chain is characterized by long supply lead-times combined with significant supply and demand uncertainties and relatively thin margins [2]. To meet the demand for fresh bananas, several governments and private agencies have started competing to provide fresh bananas to the people of Indonesia. ...
... Undoubtedly, considering the unique nature of perishable goods, this issue becomes even more critical. Therefore, there is an urgent requirement to develop a specialized and comprehensive optimal supply chain network model that caters to the specific needs of perishable products [6,7]. Additionally, ensuring cost effectiveness poses a significant challenge in the management of goods with a limited shelf life. ...
This paper focuses on optimizing the long- and short-term planning of the perishable product supply chain network (PPSCN). It addresses the integration of strategic location, tactical inventory, and operational routing decisions. Additionally, it takes into consideration the specific characteristics of perishable products, including their shelf life, inventory management, and transportation damages. The main objective is to minimize the overall supply chain cost. To achieve this, a nonlinear mixed integer programming model is developed for the multi-echelon, multi-product, and multi-period location-inventory-routing problem (LIRP) in the PPSCN. Two hybrid metaheuristic algorithms, namely genetic algorithm (GA) and multiple population genetic algorithm (MPGA), are hybridized with variable neighborhood search (VNS) and proposed to solve this NP-hard problem. Moreover, a novel coding method is devised to represent the complex structure of the LIRP problem. The input parameters are tuned using the Taguchi experimental design method, considering the sensitivity of meta-heuristic algorithms to these parameters. Through experiments of various scales, the hybrid MPGA with VNS indicates superior performance, as evidenced by the experimental results. Sensitivity analysis is conducted to examine the influence of key model parameters on the optimal objective, providing valuable management implications. The results clearly validate the efficacy of the proposed model and solution method as a reliable tool for optimizing the design problem of the PPSCN.
... Much research has also been conducted to find an efficient routing policy for perishable goods. (Meidute-Kavaliauskiene et al., 2022) addressed a VRP multi-period and multi-echelon perishable supply chain problem concerning procurement time, cycle cost, and customer satisfaction. This study presented a new form accounting for environmental considerations, cost, procurement time, and customer satisfaction, such that the total costs, delivery time, and the emission of pollutants in the network were minimized while customer satisfaction was maximized. ...
Regarding the gradual evolution of the food industry and all challenges it faces, like the high perishability of the product, managing the food industry supply chain has become an attractive issue for researchers and decision-makers. Over time the integration of uncertain aspects has continuously gained importance for managerial decision-making. Among these, the industry of yogurt products is one of the most challenging industries. In this study, we investigate the problem of production and distribution planning, scheduling, and routing in the yogurt industry supply chain network. The problem is a multi-product, single plant, multi-distribution center, multi-period, and multi-transportation track. A mixed-integer non- linear programming (MINLP) model is presented to minimize the total costs, including production, setup, overtime, unmet demand, and transportation. Besides, a robust fuzzy programming approach is applied to the problem under uncertainty. A meta-heuristic approach based on the Genetic algorithm was developed to solve the problem. In addition, the required modifications to make GA applicable are the problem mentioned. Tested experiments indicate that the proposed algorithm has an average gap of less than 0.4 percent from the optimal solution within a reasonable time. A real-world case is considered, and the proposed GA method compared to CPLEX and the results show the effectiveness of the model and the average objective function had approximately a 10% improvement.
... Sin embargo, se han llevado a cabo pocos estudios relacionados. Aspectos como la implementación de horizontes de planeación con múltiples periodos, considerando condiciones de incertidumbre (61,84), y el desarrollo de metaheurísticas unificadas para evitar la proliferación de variantes muy similares constituyen líneas de investigación que deben ser estudiadas en mayor medida en el futuro. Algunos trabajos han implementado el desarrollo del algoritmo NSGA-II (93,112) o el MOPSO (109) mejorado con características de otros algoritmos. ...
... En relación con los objetivos de estudio, la minimización de costos constituye la meta principal para los problemas planteados. Este enfoque económico ha sido acompañado en diversas investigaciones por objetivos como la minimización del impacto medioambiental causado por las emisiones de CO 2 (21,81), el balance de la carga de trabajo de los centros de distribución (82), la minimización del tiempo de recorrido (83) y la maximización de la satisfacción del cliente(84). Por otra parte, un estudio similar al presentado en(21) propone la maximización de la utilidad del personal y los clientes, además del impacto económico de la apertura de un centro de distribución, en la creación de empleo para una cadena de distribución de alimentos perecederos (85).4.2.5. ...
Context: The location and routing problem is one of the main issues in logistics and operations research oriented to minimize the system's total costs. However, in the supply chain management trend towards sustainability, most decisions introduce the optimization of several objectives simultaneously, including economic, social, and environmental perspectives, from which the multi-objective location and routing problem arises. Method: This study reviews 99 scientific articles about the multi-objective location and routing problem published between 1989 and 2022 in Scopus and Web of Science databases. The papers are selected according to specific criteria and classified based on their application. Results: This paper describes the most important characteristics of each application of the multi-objective location and routing problem in the literature. It reviews the articles according to their study objectives and solution methods to identify future research opportunities. Conclusions: First, most papers on the multi-objective location and routing problem have studied waste management, relief distribution, perishable products, green location and routing problems, cold chain, and beverage distribution. Cost minimization is the most implemented optimization objective, in combination with other goals: risk minimization, environmental impact, time minimization, customer satisfaction maximization, workload balance, and route reliability. Additionally, the problem is solved using exact and approximate multi-objective methods, with evolutionary algorithms being the most suitable for complex models. Finally, current research is oriented toward developing models under uncertainty and stochastic problems, multiple periods, time windows, multiple echelons, and heterogeneous vehicle fleets.
... e integrated performance of suppliers, manufacturers, distributors, and customers, which make up the components of the supply chain, has been studied significantly during recent years [1][2][3]. From an operational perspective, supply chain management is to integrate the suppliers, manufacturers, warehouses, and storage centers in an effective manner, so that goods are produced and distributed in the right quantities, at the right time, and in the right place in a way that minimizes the cost of the entire system while maintaining a proper level of customer service [4,5]. us, supply chain coordination is a plan that arranges the operations of supply chain members and enhances system benefits [6][7][8]. ...
... To linearize the above constraints in the problem, it is sufficient to define these equations in a linear manner by defining the binary variable y ∈ (0, 1) as follows: 4 Discrete Dynamics in Nature and Society ...
In the present study, a mathematical model is provided for inventory management in a three-level supply chain including a supplier, a manufacturer, and a distributor, taking into account the potential for product deficiency. Significant parameters such as the optimal order size for raw materials, optimal production rate, optimal allowed deficiencies at each supply chain level, the of the vehicles and the number of times the products are delivered between the supply chain components have been provided aiming at minimizing inventory management costs in the supply chain. The problem was solved using a heuristic algorithm. The proposed model is implemented for 20 different numerical examples. According to the results, the difference between the solutions obtained from the algorithm and the solutions obtained from the optimal values with the real variables is an average of 1.52%.
Managing a perishable food supply chain is a challenging task because of the short lifetime of the product and the uncertainty of demand. Perishable products require special plans with environmental, social and economic effects. Therefore, the sustainability of food supply chains plays a key role in supply chain efficiency. This paper designs a sustainable perishable food supply chain network under uncertainty. A multi-objective mixed-integer linear programming model is proposed that optimizes total costs, emissions, and shipping time to meet environmental demand. Since the demand parameter is assumed to be uncertain, the two-stage planning optimization approach under the scenario has been used. Also, the method of sum weights has been applied to make the model single-objective, and some tests are performed to select the best coefficients. In the end, deterministic and stochastic objective values compare with the Expected value, Wait and see, and Here and now methods.
