GA and SA based Evolutionary algorithm for fuzzy flexible job shop scheduling

Considering the evolutionary algorithm with the flexibility of the separate method and the high quality of the integrated method, flexible job shop scheduling problem can be solved efficiently using the evolutionary algorithm. So an evolutionary algorithm based on genetic algorithm and simulated annealing is presented, in which, genetic algorithm and an improved crossover operators are applied to job sequencing, simulated annealing is used to machine assigning and two parts interacts in the evolutionary process. The experimental results show that the proposed algorithm has better performance than other algorithms from literature.