Abstract
In this paper, job shop scheduling problems with fuzzy duedate and fuzzy processing time 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 afreement index. For solving the formulated fuzzy job shop scheduling problems, a genetic algorithm is proposed ny incorporating the concept of similarity among individuals into the genetic algorithms using the Gantt chart. As illustrative numerical examples, both 6×6 and 10×10 job shop scheduling problems with fuzzy duedate and fuzzy processing time are considered, and the feasibility and effectiveness of the proposed method are demonstrated.
