A genetic algorithm for flow shop scheduling with fuzzy processing time and due date

Production scheduling plays an important role in enterprises´ activities, and flow shop is a typical process in many factories. The fuzzy numbers is used to denote the uncertainty of processing time in flow shop scheduling problem, and the multiple objectives´ scheduling model is developed for flow shop scheduling problems with fuzzy processing time. The multiple objectives is converted into single one by weighted method, and the fuzzy optimal problem then transformed to determinate one by Zimmermann algorithm. An efficient genetic algorithm suitable for solving the problems is proposed. As illustrative numerical examples, 10×5 flow shop problems with fuzzy processing time are considered, and many simulations are investigated. The simulated results show the effectiveness of the proposed method.