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In this paper, an efficient hybrid genetic algorithm (GA) algorithm is proposed to solve the flexible job shop scheduling problem (FJSSP) problem with machine status constraint. According to the machine status in the actual production workshop, the machine available constraint is added to the scheduling. The mathematical model is designed in the paper for FJSSP with the machine available constraint. The GA algorithm is applied to produce initial solution and tabu search (TS) is used to promote local search ability. The operation-based representation method, crossover and mutation operation are utilized to increase the performance. The computational experiments are conducted to testify the efficiency of the proposed algorithm.

An Effective Hybrid Genetic Approach for Flexible Job Shop Scheduling Problem with Machine Status Constraint