Volume 19, Issue 4 (12-2022)                   jor 2022, 19(4): 37-61 | Back to browse issues page


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Seyedi I, Hamedi M, Tavakkoli-Moghaddam R. Enhancing the Search Capability of the Imperialist Competitive Algorithm for Truck Scheduling Problem in the Cross-Docking System. jor 2022; 19 (4) :37-61
URL: http://jamlu.liau.ac.ir/article-1-1993-en.html
Department of Industrial Engineering, Payame Noor University, Tehran, Iran
Abstract:   (1670 Views)
In today's distribution environment, cross-docking has attracted the attention of many researchers due to its vital role in reducing costs in supply chains. The cross-docking system reduces the cost of distribution by eliminating storage and sorting. In this article, we look at the issue of truck scheduling in a cross-docking system. According to the research literature, the issue of cross-docking scheduling is one of the Np-hard problems, so in this paper, a new hybrid approach to solve this problem is presented. The Imperial Competition Algorithm (ICA) is a socio-political algorithm inspired by imperialist competition. However, when searching in a complex environment, its efficiency is significantly reduced, and this limitation confines the algorithm for achieving a good solution. This paper introduces a new search mechanism to solve this problem. This algorithm is based on the principal component analysis (PCA) method in which PCA actually extracts a low-dimensional set of features from a high-dimensional set to help record more information with fewer variables. This is why the method is called PCICA. The results from the new algorithm were compared with ICA, SA, and GA methods. Results show that PCICA performs significantly better than others and can find reasonable solutions.
Full-Text [PDF 1301 kb]   (374 Downloads)    
Type of Study: Research | Subject: Special
Received: 2021/12/18 | Accepted: 2022/06/8

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