The multiobjective job shop scheduling problem with mean tardiness and the maximum tardiness as the objectives is addressed. A genetic local search algorithm is proposed with several features. First, it uses a dispatching rule-based genome encoding scheme, and the encoded dispatching rules are chosen carefully. Second, its mating selection mechanism combines the advantages of two representative ones in the literature. Third, it enhances a recently proposed population-based local search procedure. The benefits of the proposed idea are verified through experiments on a public benchmark problem set. In the experiments, the proposed algorithm is also shown to significantly outperform a recent algorithm specific to the multiobjective job shop scheduling problem.
|出版狀態||已發佈 - 2006 十二月 1|
|事件||36th International Conference on Computers and Industrial Engineering, ICC and IE 2006 - Taipei, 臺灣|
持續時間: 2006 六月 20 → 2006 六月 23
|其他||36th International Conference on Computers and Industrial Engineering, ICC and IE 2006|
|期間||2006/06/20 → 2006/06/23|
ASJC Scopus subject areas