Method for GA-based solution to job shop scheduling optimization
基于遗传算法的作业车间调度优化求解方法

This paper proposed a new encoding method and decoding method with the matrix form for a solution to genetic algorithm-based job shop scheduling problem.Based on a specific problem,designed a job activities' number-dependent coding of chromosomes and adopted the matrix decoding.As a result,codes by the new encoding method accord with the job scheduling schemed one-to-one were able to match multiple cross operators without a special design of operators.Result from a case study show that the genetic algorithm with the help of new encoding method presented a powerful ability and was able to effectively solve job shop scheduling problems.To show merits of the new encoding and decoding method,a comparison of different sized job shop scheduling problems in terms of job activity duration,sequence,and scheduling schemes,showed that with the help of the proposed method the genetic algorithm is encouraging,with solutions found through simple operations and fast convergence.