| Article ID: | iaor2006465 |
| Country: | China |
| Volume: | 36 |
| Issue: | 3 |
| Start Page Number: | 317 |
| End Page Number: | 321 |
| Publication Date: | Jun 2004 |
| Journal: | Journal of Nanjing University of Aeronautics and Astronautics |
| Authors: | Li Jin, Lou Peihuang |
| Keywords: | heuristics |
Genetic algorithm is widely applied to the job shop scheduling problem (JSSP) and is proved to be a better solution for JSSP compared with most conventional solutions. However, several problems must be solved by achieving a performance-superior GA-based solution for JSSP, of which deadlock problem is a very tough obstacle. This paper analyses three methods for overcoming the deadlock problem. Finally, statistical results of the GA-based solutions for JSSP and conclusions are given.