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

2020 ◽  
pp. 1-17
Author(s):  
Ming Li ◽  
Bin Su ◽  
Deming Lei

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.

2014 ◽  
Vol 643 ◽  
pp. 374-379
Author(s):  
Hua Wei Yuan ◽  
Yuan Wei Jing ◽  
Tao Ren

This paper considers the m-machine flow shop problem to minimize weighted completion time. A heuristic algorithm is presented to deal with the problem for large size problem. At the end of the paper, some numerical experiments show the effectiveness of the heuristic.


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