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Research on Cell Manufacturing Facility Layout Problem Based on Improved NSGA-II

Yanlin Zhao1, 2, *, Jiansha Lu1, Qing Yan1, Lili La1, Lili Xu1

1 Zhejiang University of Technology, Hangzhou, 310014, China.
2 Panzhihua University, Panzhihua, 617000, China.

* Corresponding Author: Yanlin Zhao. Email: email.

Computers, Materials & Continua 2020, 62(1), 355-364. https://doi.org/10.32604/cmc.2020.06396

Abstract

With the rapid development of the individualized demand market, the demand for manufacturing flexibility has increased over time. As a result, a cell manufacturing system suitable for many varieties and small batches has been produced. With the goal of minimizing the area and logistics handling volume, and considering the arrangement order of facilities and channel constraints, a mathematical model was established, and the problem was solved by improved NSGA-II. After non-dominated sorting, traditional NSGA-II will cross-operate the individuals with the best sorting to generate new individuals. Such a selection strategy is extremely easy to fall into the local optimal solution. The improved NSGA-II is to improve the original selection operation, which is to select the first half of the excellent individuals in the non-dominated sorting into the cross operation, and then select the last sorted ones of the remaining individuals into the cross operation, and combine the best and the worst ones into the cross operation. Finally, an example is given to simulate and improve the solution of NSGA-II and NSGA-II. The simulation results indicate that the improved NSGA-II population shows more obvious diversity, it is easier to jump out of the local optimal solution than NSGA-II, and the satisfactory layout scheme of manufacturing cells is obtained. Therefore, it is more effective to use improved NSGA-II to solve the problem of manufacturing cell layout.

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Cite This Article

Y. Zhao, J. Lu, Q. Yan, L. La and L. Xu, "Research on cell manufacturing facility layout problem based on improved nsga-ii," Computers, Materials & Continua, vol. 62, no.1, pp. 355–364, 2020.

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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