Applying the differential evolution algorithm with the fuzzy selection mechanism for the flexible job shop scheduling problem

This paper proposed the new algorithm which applied the fuzzy selection mechanism with the differential evolution (DE) algorithm for solving the flexible job shop scheduling problem (FJSP). The proposed algorithm is mainly based on the concept of the DE algorithm. In the first step, the population is created by randomly using the population generation rules. Next step, this paper utilized the fuzzy selection mechanism to select the proper machine according to the number of operation load and the machine processing time load. The POX and the uniform crossover operation are used to enhance the exploitation capability in the third step. The finally, the local search based on the critical path operation is applied to explore the neighbor solution in the surrounding areas of the best population. The experimental result shows that, the proposed algorithm is best among the other comparison algorithm.

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