| Article ID: | iaor20033144 |
| Country: | China |
| Volume: | 17 |
| Issue: | 2 |
| Start Page Number: | 161 |
| End Page Number: | 166 |
| Publication Date: | Apr 2002 |
| Journal: | Journal of Systems Engineering and Electronics |
| Authors: | Da Qingli, Chen Weida |
| Keywords: | genetic algorithms |
The job-shop scheduling problem is a well-known NP-hard problem, but job-shop scheduling with variable tools is a more common problem. In recent years genetic algorithms have been used in the field of job-shop scheduling. In this paper, we analyze the characteristic of the job-shop scheduling with variable tools and establish the optimal model. We present a bilevel genetic algorithm and newly design genetic coding scheme, and discuss selection, crossover and mutation operator of the bilevel genetic algorithm. Through numerical experiment analysis and verification, the bilevel genetic algorithm is effective and feasible to solve the job-shop scheduling with variable tools.