An ERNSGA-III algorithm for the production and distribution planning problem in the multiagent supply chain
An ERNSGA-III algorithm for the production and distribution planning problem in the multiagent supply chain
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DOI：
10.1111/itor.12654
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发表时间：
2019-03
期刊：
影响因子：
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通讯作者：
Ali Gharaei;F. Jolai
中科院分区：
文献类型：
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作者：
Ali Gharaei;F. Jolai
随着供应链边界的不断扩大，特别是当供应链中的一些成员为了自身的利益而寻求利益时，产业中出现了新的问题。在文献中，这种情况被称为多智能体问题，其中每个智能体都有自己的一套工作和目标。本文从制造商、分销商和客户三个代理人的角度研究了多地点供应链中的集成生产调度和分销问题。针对该问题的复杂性，提出了一种基于进化的参考点确定的第三代非支配排序遗传算法（ERNSGA-III）。该算法对经典的NSGA-III算法进行了改进，并在选择操作中采用了一种基于Bees算法的参考点确定方法。一些统计测试进行比较，该算法与其他三种算法在文献中。实验结果表明，该算法比其他算法更有效.
Nowadays, new issues have been emerged in industry by increasing the supply chain boundaries, especially when some supply chain members seek their own interests. In the literature, this case is referred to as a multiagent problem in which each agent has his/her own set of jobs and objectives. Here, an integrated production scheduling and distribution problem in a multisite supply chain is investigated from the three-agent perspective of the manufacturer, distributor, and customer. Due to the complexity of the problem, a novel evolutionary-based reference point determination of the third version of the non-dominated sorting genetic algorithm (ERNSGA-III) is proposed. In this algorithm, some modifications to the classic version of NSGA-III have been made and a novel reference point determination method based on Bees algorithm is used in the selection operation. Some statistical tests are performed to compare the proposed algorithm with three other algorithms in the literature. The results show that the proposed algorithm is more effective than other algorithms.