A two-stage hybrid memetic algorithm for multiobjective job shop scheduling

In this paper we address multiobjective job shop scheduling problems. After several decades of research in scheduling problems, a variety of heuristics have been developed. The proposed algorithm is a hybrid of three frequently applied ones: the dispatching rule, the shifting bottleneck procedure, and the evolutionary algorithm. It is a two-stage algorithm, which integrates a rule-based memetic algorithm in the first stage and a re-optimization procedure of shifting bottleneck in the second. We conduct experiments using benchmark instances found in the literature to assess the performance of the proposed method. The experimental results show that the proposed method is effective and efficient for multiobjective scheduling problems.

► A two-stage algorithm integrating dispatching rules, memetic algorithm (MA), and the shifting bottleneck (SB) heuristic is proposed.
► A dominance-based multiobjective MA with rule-weight encoding generates high-quality schedules efficiently.
► The SB uses an MA with operation-based encoding as the subproblem solver to further optimize the schedules.
► Performance is verified by 34 JSSP and FJSSP instances with hypervolume and epsilon-indicator as metrics.