Hybrid Search Strategy in Fuzzy Job Shop Scheduling

A new hybrid strategy is proposed for fuzzy job shop scheduling problems,which adopts parallel genetic algorithm as the global search algorithm.According to the characteristics of the Job Shop scheduling solutions,we propose a new method of neighbor selection based on the critical operation,and use a taboo search(TS)algorithm based on the neighbor selection as the local search algorithm.The local searching ability of genetic algorithm is enhanced.Experimental results on 13 hard problems of benchmarks show that,in a short time,the hybrid search strategy increases 4.67% on the average agreement index than that of parallel genetic algorithms,and increases 5.76% than that of Taboo Search Algorithm with Back jump tracking(TSAB).The adopted taboo search algorithms improve the local searching ability of the genetic algorithm,proving the effectiveness of the presented hybrid strategy.