Article ID: | iaor2002207 |
Country: | Netherlands |
Volume: | 40 |
Issue: | 3 |
Start Page Number: | 191 |
End Page Number: | 200 |
Publication Date: | Jul 2001 |
Journal: | Computers & Industrial Engineering |
Authors: | Zhou Hong, Feng Yuncheng, Han Limin |
Keywords: | genetic algorithms, job shop |
Scheduling for the job shop is very important in both fields of production management and combinatorial optimization. However, it is quite difficult to achieve an optimal solution to this problem with traditional optimization methods owing to the high computational complexity (NP-hard). Genetic algorithms (GA) have been proved to be effective for a variety of situations, including scheduling and sequencing. Unfortunately, its efficiency is not satisfactory. In order to make GA more efficient and practical, the knowledge relevant to the problem to be solved is helpful. In this paper, a kind of hybrid heuristic GA is proposed for problem