Genetic Algorithm With Simulated Annealing For Resolving Job Shop Scheduling Problem

In the general environment of the new round of technological revolution,market demand is shifting to individualization and diversification,and the production model of enterprises is gradually transforming to multi-variety,medium and small batches.At this time,the role of the production scheduling system is even more important.This article first introduces the current research status of production scheduling problems at home and abroad and some commonly used algorithms to solve production scheduling problems in enterprise production activities,mainly the genetic algorithm(GA)and simulated annealing algorithm to solve the specific operation process and existing problems of workshop scheduling Introduce,and finally introduce in detail the specific implementation process of an improved genetic simulated annealing algorithm(GASA)proposed in this paper.This article has carried out an in-depth study of the workshop scheduling problem from the following three aspects:Firstly,in view of the limitations of traditional workshop scheduling research,this paper establishes a workshop scheduling model in the traditional scheduling model that minimizes the maximum completion time,minimizes the load of key machines,and minimizes the total load of machines.Secondly,in this paper,the improved genetic simulated annealing algorithm(GASA)is used to solve the production scheduling problem.This algorithm is based on the genetic algorithm.In the process of operation,elitist reservation strategy,non dominated sorting,simulated annealing and other operations are added.The hybrid algorithm not only gives full play to the advantages of fast convergence speed of genetic algorithm and wide search range of simulated annealing algorithm,but also overcomes the premature convergence of the former and the premature convergence of the latter The problem of slow convergence speed improves the overall convergence speed and search efficiency of the algorithm.Finally,the algorithm proposed in this paper is compared with the simulation experimental results of the algorithms in relevant literature,and the experimental results show that the algorithms proposed in this paper have greater advantages.By investigating the production data of a heavy industry enterprise and combining with the actual situation of the job shop scheduling of the enterprise,the actual shop scheduling system is developed and solved by using the GASA algorithm,which verifies the feasibility,effectiveness and rationality of the improved algorithm in practical application.