Abstract
Permutation flow shop scheduling problem (PFSP) exists widely in the manufacturing system. The traditional researches often considered setup time as one part of processing time. However, this assumption does not meet the requirement of the “more varieties, small batches” production model. Therefore, the PFSP with setup time becomes an urgent problem to be solved. This paper proposes an effective hybrid algorithm combining genetic algorithm and variable neighborhood search together. Several neighborhood structures are employed. A set of benchmarks has been used to evaluate its performance. By comparing with some famous algorithms, the merits of proposed method can be shown clearly.
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