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首页> 外文期刊>International journal of production economics >A bi-objective interval-stochastic robust optimization model for designing closed loop supply chain network with multi-priority queuing system
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A bi-objective interval-stochastic robust optimization model for designing closed loop supply chain network with multi-priority queuing system

机译：具有多优先级排队系统的闭环供应链网络设计的双目标区间随机鲁棒优化模型

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摘要

This paper presents a bi-objective optimization model for designing a closed loop supply chain (CLSC) network under uncertainty in which the total costs and the maximum waiting times in the queue of products are considered to minimize. A general multi-priority and multi-server queuing system for parallel processing execution is proposed. Also a new hybrid solution approach is introduced based on interval programming, stochastic programming, robust optimization approach, and fuzzy multi-objective programming. Furthermore, a meta-heuristic algorithm called self-adaptive imperialist competitive algorithm (SAICA) is put forward for the given problem. Then, in order to evaluate the quality of the solutions obtained by this algorithm, a lower bound procedure is investigated. Finally, various computational experiments are carried out to assess the proposed model and solution approaches. (C) 2015 Elsevier B.V. All rights reserved.
机译：本文提出了一种在不确定性条件下设计闭环供应链（CLSC）网络的双目标优化模型，该模型考虑了总成本和产品队列中的最大等待时间，以将其最小化。提出了一种用于并行处理执行的通用多优先级和多服务器排队系统。还引入了一种新的混合解决方案方法，该方法基于区间规划，随机规划，鲁棒优化方法和模糊多目标规划。此外，针对给定的问题，提出了一种称为启发式帝国竞争算法（SAICA）的元启发式算法。然后，为了评估该算法获得的解的质量，研究了下界过程。最后，进行了各种计算实验以评估所提出的模型和解决方案方法。 （C）2015 Elsevier B.V.保留所有权利。

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