Abstract

Flexible job shop scheduling problem is a very important research in the field of combinatorial optimization. An improved ant colony algorithm for multi-objective flexible job shop scheduling problem is presented in this paper. The rule of our algorithm is described from the following aspects: local update, global update, trail intensities, solution set, local search, suitable parameters. 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.

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