A novel cultural algorithm based on differential evolution for hybrid flow shop scheduling problems with fuzzy processing time

Authors:
Qun Niu;Tingting Zeng;Zhuo Zhou
Affiliations:
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China;School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China;School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China
Venue:
IUKM'11 Proceedings of the 2011 international conference on Integrated uncertainty in knowledge modelling and decision making
Year:
2011

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Abstract

Considering the imprecise or fuzzy nature of the data in realworld problems, this paper proposes a novel cultural algorithm based on differential evolution (CADE) to solve the hybrid flow shop scheduling problems with fuzzy processing time(FHFSSP). The mutation and crossover operations of differential evolution (DE) are introduced into cultural algorithm (CA) to enhance the performance of traditional CA. Experimental results demonstrate that the proposed CADE method is more effective than CA, particle swarm optimization (PSO) and quantum evolution algorithm (QA) when solving FHFSSP.