可持续闭环供应链网络设计的多目标模糊规划问题

Multi-objective fuzzy programming for sustainable closed-loop supply chain network design

中文关键词  可持续性；供应链  网络设计  模糊规划  遗传算法  鲸鱼优化算法

英文关键词  sustainability  supply chains  network design  fuzzy planning  genetic algorithm  whale optimization algorithm

中文摘要

      为解决不确定条件下可持续闭环供应链网络设计的问题, 以成本和环境影响最小、社会影响最大为目标, 建立带有模糊参数的多目标闭环供应链网络规划模型. 首先采用Me测度处理相关模糊目标和参数, 并运用加权增广Epsilon-约束方法解决多目标问题, 在此基础上设计一种基于[0,1]随机数的双层编码遗传鲸鱼(GA-WOA)混合算法进行求解, 然后构造多个不同规模算例, 将混合算法求解结果与CPLEX、遗传算法的求解结果进行对比, 结果证明该编码方式和混合算法具有合理性. 最后针对模型的多个参数变化进行分析, 以验证所建模型的可行性.

英文摘要

      In order to solve the problem of sustainable closed-loop supply chain network design under uncertainty, a multi-objective closed-loop supply chain network optimization model with fuzzy parameters was established with the objective of minimizing cost and environmental impact and maximizing social impact. Firstly, Me fuzzy measure is used to cope with the fuzzy objectives and parameters, then the weighted augmented Epsilon-constrained method is employed to solve the multi-objective problem. On this basis, a genetic-whale (GA-WOA) hybrid algorithm based on [0,1] random number is designed to solve the problem, afterward, several different scale examples are constructed, then the results of the hybrid algorithm are compared with the results of CPLEX and genetic algorithm. The results show that the coding method and the hybrid algorithm are reasonable. Finally, variations of multiple parameters of the model are analyzed to verify the feasibility of the model.