A Hybrid Evolutionary Algorithm for Flexible Job-shop Scheduling Problem

摘要

Flexible Job-shop Scheduling Problem (FJSP) is an extension of the classical JSP, which allows an operation to be processed by any machine from a given set of machines. Scheduling for the FJSP is very important due to the rapid development of new processes and technologies and the growing consumer demand for variety. Appreciating the importance of FJSP and the importance of scheduling for competitive manufacturing, optimization of the problem has been taken up in the present task. The complexity of the FJSP can be well dealt with by the use of Particle Swarm Optimization (PSO) algorithm. However this method has a limitation of getting trapped with local optima. In the present work, a hybrid methodology (PSO+GA) has been used to avoid this pitfall. The results obtained show that the proposed algorithm is a viable and effective approach for the multi-objective FJSP.