An improved multi-objective genetic algorithm for solving flexible job shop problem

In this paper, a solution searching strategy called advanced solution extraction is proposed to assistant multi-objective optimizer for solving flexible job shop problem (FJSP). The goal of this problem is to finish all jobs within minimal critical machine workload, total workload and executing time, simultaneously. For comparing proposed with related work, experiments employ three benchmarks. Each benchmark includes numbers of heterogeneous processors and different jobs for completion. From the results, the proposed method can find more optimal solutions than related work.