A bi-objective multi-period closed-loop supply chain network under uncertain demand

Marjan Olfati, N. Javadian
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引用次数: 1

Abstract

Due to the competitive environment, supply chain management is an important subject in the world of economy. It affects all of the activities including products manufacturing, flow between facilities and costs. In this research, a mixed-integer linear programming model is considered which included supplier, plants, demand markets, collection centres, and disposal centre. The closed-loop supply chain model is bi-objective. So, it is solved by the e-constraint method and non-dominated sorting genetic algorithm-II. In order to improve the meta-heuristic algorithm's efficiency, its parameters are tuned by Taguchi method. Afterward, the different dimensions of the model are considered and the problem is rewritten as a single-objective model and solved by LINGO software and the genetic algorithm using MATLAB software to compare the efficiency of the LINGO and meta-heuristic algorithm. In small-scale problems, solving by LINGO software and in large-scale problems, solving by meta-heuristic algorithms are more efficient.
需求不确定条件下的双目标多周期闭环供应链网络
由于竞争的环境,供应链管理是世界经济中的一个重要课题。它影响所有的活动,包括产品制造,设施之间的流动和成本。在本研究中,考虑了一个混合整数线性规划模型,其中包括供应商、工厂、需求市场、收集中心和处理中心。闭环供应链模型是双目标的。因此,采用e约束法和非支配排序遗传算法求解。为了提高元启发式算法的效率,采用田口法对其参数进行了调优。然后,考虑模型的不同维度,将问题改写为单目标模型,利用MATLAB软件将LINGO软件和遗传算法进行求解,比较LINGO算法和元启发式算法的效率。在小规模问题中,使用LINGO软件求解,在大规模问题中,使用元启发式算法求解效率更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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