Multi-objective flexible job shop schedule based on improved ant colony algorithm

Flexible job shop scheduling problem is a very important research in the field of combinatorial optimization. It is also important for practical production. A method for solving multi-objective flexible job shop scheduling problem based on ant colony algorithm is presented in this paper. Ant colony algorithm is improved from the following aspects in this paper: The number of subsets is defined by the number of jobs; A new method of constructing allowed set is given in this paper; An effective local search method is applied in the improved ant colony algorithm for searching a better scheduling. The problem of choosing suitable parameters for the improved ant colony algorithm is also discussed in this paper. The algorithm we presented is validated by practical instances. The results obtained have shown the proposed approach is feasible and effective for the multi-objective flexible job shop scheduling problem.