Abstract
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.
| Original language | English |
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| Pages | 1764-1775 |
| Number of pages | 12 |
| Publication status | Published - 2006 |
| Externally published | Yes |
| Event | 36th International Conference on Computers and Industrial Engineering, ICC and IE 2006 - Taipei, Taiwan Duration: 2006 Jun 20 → 2006 Jun 23 |
Other
| Other | 36th International Conference on Computers and Industrial Engineering, ICC and IE 2006 |
|---|---|
| Country/Territory | Taiwan |
| City | Taipei |
| Period | 2006/06/20 → 2006/06/23 |
Keywords
- Dispatching rules
- Job shop scheduling
- Multiobjective evolutionary algorithms
ASJC Scopus subject areas
- Industrial and Manufacturing Engineering