Article ID: | iaor20021183 |
Country: | South Korea |
Volume: | 26 |
Issue: | 2 |
Start Page Number: | 59 |
End Page Number: | 68 |
Publication Date: | Jun 2001 |
Journal: | Journal of the Korean ORMS Society |
Authors: | Park Byung Joo, Kim Hyun Soo |
Keywords: | job shop, genetic algorithms |
The job shop scheduling problem is not only NP-hard, but is one of the well known hardest combinatorial optimization problems. The goal of this research is to develop an efficient scheduling method based on hybrid genetic algorithm to address job shop scheduling problem. In this scheduling method, generating method of initial population, new genetic operator, selection method are developed. The scheduling method based on genetic algorithm are tested on standard benchmark job shop scheduling problem. The results are compared with another genetic algorithm-based scheduling method. Compared to traditional genetic algorithm, the proposed approach yields significant improvement at a solution.