Solving the Flexible Job Shop Scheduling Problems Based on the Adaptive Genetic Algorithm

Considering the flexible job shop scheduling problem (FJSSP) more accorded with practice, a correspondent model is established and the adaptive genetic algorithm is used to solve it. According to the features of the model (machines are optional), three factors: the processing time, the completion time of previous operation and the idle time of current machine are synthetically considered for choosing a suitable machine in the decoding process of the chromosomes. The simulating experiments demonstrate that the proposed scheduling algorithm can get better solutions than previous algorithms in large scale FJSSP.