Discrete Gray Wolf Optimizer for Solving Distributed Permutation Flowshop Scheduling Problem DOI
Shuilin Chen, Jianguo Zheng

Concurrency and Computation Practice and Experience, Journal Year: 2025, Volume and Issue: 37(9-11)

Published: April 15, 2025

ABSTRACT Distributed manufacturing has become a mainstream production mode in economic globalization. A discrete gray wolf optimizer (DGWO) is proposed to solve the distributed permutation flowshop scheduling problem (DPFSP) minimize makespan. First, an extended Nawaz‐Enscore‐Ham2 (ENEH2) and randomly generated hybrid initialization method are used enhance diversity ergodicity of population. Second, population update mechanism for characteristics solved balance exploration exploitation. The variable neighborhood descent search strategy further improve quality solution. Finally, Wilcoxon signed rank Friedman test statistical comparison analysis. To verify performance DGWO, simulation experiments conducted on different scales instances compared with various methods demonstrate advantages DGWO solving DPFSP.

Language: Английский

Discrete Gray Wolf Optimizer for Solving Distributed Permutation Flowshop Scheduling Problem DOI
Shuilin Chen, Jianguo Zheng

Concurrency and Computation Practice and Experience, Journal Year: 2025, Volume and Issue: 37(9-11)

Published: April 15, 2025

ABSTRACT Distributed manufacturing has become a mainstream production mode in economic globalization. A discrete gray wolf optimizer (DGWO) is proposed to solve the distributed permutation flowshop scheduling problem (DPFSP) minimize makespan. First, an extended Nawaz‐Enscore‐Ham2 (ENEH2) and randomly generated hybrid initialization method are used enhance diversity ergodicity of population. Second, population update mechanism for characteristics solved balance exploration exploitation. The variable neighborhood descent search strategy further improve quality solution. Finally, Wilcoxon signed rank Friedman test statistical comparison analysis. To verify performance DGWO, simulation experiments conducted on different scales instances compared with various methods demonstrate advantages DGWO solving DPFSP.

Language: Английский

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