Abstract

AbstractConsidering the imprecise or fuzzy nature of the data in real-world 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.KeywordsCultural algorithmDifferential evolutionHybrid flow shop schedulingMakespanFuzzy processing time

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