| Article ID: | iaor20021185 |
| Country: | China |
| Volume: | 25 |
| Issue: | 5 |
| Start Page Number: | 99 |
| End Page Number: | 102 |
| Publication Date: | Oct 2000 |
| Journal: | Journal of Kunming University of Science and Technology |
| Authors: | Zhai Wenbin, Fan Yujin, Li Zhekun |
| Keywords: | genetic algorithms, job shop |
The problem of dynamic job-shop scheduling is studied and an improved genetic algorithm (GA) for solving it is proposed. Firstly, the code is encoded with a vector based on a heuristic approach. Secondly, competition between genetic populations is introduced into the GA so that they can evolve and develop into an advanced balanced state. In this way, the performance of the scheduling is optimized. Thirdly, the dynamic production scheduling is evaluated by a scheduling function and production chart. Finally, the simulation results show that the improved GA is effective in complex scheduling.