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Fuzzy green vehicle routing problem for designing a three echelons supply chain

机译:设计三个梯队供应链的模糊绿色汽车路由问题

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In this study, a three-echelon fuzzy green vehicle routing problem (3E-FGVRP) is considered for designing a regional agri-food supply chain on a time horizon. To account for the variability associated with the quantities requested by customers, it is assumed that the demands are fuzzy numbers simulated by a time-dependent algorithm. Moreover, the vehicle fleet and distribution centres are considered with a defined capacity. The credibility theory of fuzzy sets is used to implement a multi-objective fuzzy chance-constrained programming model, where the total costs and carbon emissions are minimised. The resolution of the 3E-FGVRP is conducted by using a non-dominated sorting genetic algorithm. The multiple-criteria decision-making ELECTRE III method is applied to select the best solutions belonging to each Pareto front. Finally, the validity of the model is demonstrated by performing an optimisation procedure with three different initial random sets of populations. The application of the model to a case study of the Sicilian agri-food context confirms the robustness of the model, and the optimal configurations of the three-echelon supply chain can be found. (C) 2020 Elsevier Ltd. All rights reserved.
机译:在这项研究中,考虑了一个三个梯度模糊的绿色载体路线问题(3E-FGRP)在时间范围内设计区域农产品供应链。为了考虑与客户所需数量相关的可变性,假设需求是通过时间相关算法模拟的模糊数。此外,车队和配送中心被认为是规定的容量。模糊集的可信度理论用于实施多目标模糊机会约束编程模型,其中总成本和碳排放最小化。通过使用非主导的分类遗传算法进行3E-FGVRP的分辨率。应用多标准决策电气III方法来选择属于每个帕累托前部的最佳解决方案。最后,通过使用三种不同的初始随机组群体执行优化过程来证明模型的有效性。该模型在Sicilian Agri-Food上下文的案例研究中的应用证实了模型的鲁棒性,并且可以找到三梯队供应链的最佳配置。 (c)2020 elestvier有限公司保留所有权利。

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