| Article ID: | iaor20011765 |
| Country: | Netherlands |
| Volume: | 36 |
| Issue: | 2 |
| Start Page Number: | 325 |
| End Page Number: | 341 |
| Publication Date: | Apr 1999 |
| Journal: | Computers & Industrial Engineering |
| Authors: | Sakawa Masatoshi, Mori Tetsuya |
| Keywords: | fuzzy sets |
In this paper, by considering the imprecise or fuzzy nature of the data in real-world problems, job-shop scheduling problems wih fuzzy processing time and fuzzy duedate are formulated and a genetic algorithm which is suitable for solving the formulated problems is proposed. On the basis of the agreement index of fuzzy duedate and fuzzy completion time, the formulated fuzzy job-shop scheduling problems are interpreted so as to maximize the minimum agreement index. For solving the formulated fuzzy job-shop scheduling problems, an efficient genetic algorithm is proposed by incorporating the concept of similarity among individuals into the genetic algorithms using the Gannt chart. As illustrative numerical examples, both 6×6 and 10×10 job-shop scheduling problems with fuzzy duedate and fuzzy processing time are considered. Through the comparative simulations with simulated annealing, the feasibility and effectiveness of the proposed method are demonstrated.