A Solution To The JSP Based On The Genetic Algorithm

Job Shop scheduling problem is the core of manufacturing execution systems. It can improve the enterprise resource utilization and improve the overall quality of products and shorten product delivery time, lower production costs. It has very important significance to improve enterprise in a market economy's competitiveness. Since the actual job shop scheduling problems have the characters of complex, dynamic random binding, multi-objective characteristics, the academic and industry pay much attention to it. Research shows that the Job Shop scheduling problem is NP-hard problem, and there is no precise algorithm for the optimal solution, it can only be obtained similar to the optimal solution.Genetic Algorithms is a model of Darwin's natural selection and biological evolution, it is a kind of global optimization search algorithm. Genetic Algorithms for its simple common, strong robustness, parallel processing capability, search the global optimum speed, and so notable feature, is widely used in the NP problem solving. GA can be used in genetic algorithms Job Shop scheduling problem, we can use genetic algorithm's powerful global search capabilities, in the solution space and in the large-scale search for optimal solutions; At the same time, because genetic algorithm have the characters of the implicit parallel processing capability and strong robustness, it can reduce the time to solve problems and improve the efficiency of solving.However, there are obviously inadequate when using the genetic algorithm to solve the Job Shop scheduling problem. According to the lack of genetic algorithm, we introduce the simulated annealing, according to both the advantages and disadvantages, we put forward the idea of hybrid genetic algorithm. Through introducing the details of the combination of the two algorithms, we make full use of the advantages of two algorithms, and enhance the local search ability of genetic algorithm; Then based on the problems that may arise at the actual job shop scheduling, we use hybrid genetic algorithm to the actual scheduling problem, then design the hybrid genetic algorithm coding method and the corresponding genetic operator to solve the job shop scheduling problem, and introduce the details of the combination of the two algorithms; Finally, give the Job Shop scheduling system design ideas, and use some parts of code and the picture of the system to show the system.