A collaborative evolutionary algorithm for multi-objective flexible job shop scheduling problem

Flexible job shop scheduling problem (FJSP) is a very important problem in the modern manufacturing system. It is an extension of the classical job shop scheduling problem. Because of the importance of FJSP and the multiple objectives requirement from the real-world production, this research focuses on the multi-objective FJSP. This paper proposes a collaborative evolutionary algorithm (CEA) based on Pareto optimality to solve the multi-objective FJSP. Experimental studies have been used to test the approach. And the experimental results show that the proposed approach is a promising and very effective method on the research of multi-objective FJSP.