Genetic Algorithm For Job Shop Scheduling Optimization Problems

The Job-Shop scheduling is one of the cores and key points of ManufacturingExecution System research. It is significant for improving the utilizationof the enterprise resources, enhancing the product quality, shortening thedelivery periods, reducing the produce cost, and raising the enterprisecompetitive power in the market economy. Since the Job-Shop scheduling hasthe characters of complex, dynamic ,random, bounded, multi-objectives and soon , the general algorithms could not solve this kind of NP problem .As an uncertain stochastic optimal algorithm, GA had been applied in allkinds of fields in the past 20 years. And because of its independence, globaloptimization and implicit parallelism, GA has been applied to solve thecomplex workshop scheduling problem successfully.In connected with the Job Shop scheduling problem, the paper proposes asolution method based on GA and gives the encoding method of chromosome andthe corresponding operators are given. The encoding method greatly simplifiesthe operators in GA, and also achieves the algorithm simulation by using theMATLAB programming.