A novel imperialist competitive algorithm for fuzzy distributed assembly flow shop scheduling

Article type: Research Article

Authors: Li, Ming | Su, Bin | Lei, Deming^{; *}

Affiliations: School of Automation, Wuhan University of Technology, Wuhan, China

Correspondence: [*] Corresponding author. Deming Lei, School of Automation, Wuhan University of Technology, Wuhan 430070, China. E-mail: deminglei11@163.com.

Abstract: Assembly flow shop scheduling problem with DPm → 1 layout has important applications in various manufacturing systems and has been extensively considered in single factory; however, this problem with fuzzy processing time is seldom studied in multiple factories. In this paper, fuzzy distributed assembly flow shop scheduling problem (FDAFSP) is considered, in which each factory has DPm → 1 layout, and an imperialist competitive algorithm with empire cooperation (ECICA) is developed to minimize fuzzy makespan. In ECICA, an adaptive empire cooperation between the strongest empire and the weakest empire is implemented by exchanging computing resources and search ability, historical evolution data are used and a new imperialist competition is adopted. Numerical experiments are conducted on various instances and ECICA is compared with the existing methods to test its performance. Computational results demonstrate that ECICA has promising advantages on solving FDAFSP.

Keywords: Assembly flow shop scheduling, distributed scheduling, imperialist competitive algorithm, fuzzy makespan

DOI: 10.3233/JIFS-201391

Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 3, pp. 4545-4561, 2021