Research On Flexible Job Shop Scheduling Problem Based On Improved NSGA-Ⅱ

The flexible job shop scheduling problem is a new type of problem developed on the basis of the JSP.This problem is to add a series of constraints that fit the real production shop in the process of job shop scheduling,so that its solution is improving its production efficiency,which is the need of enterprise development.As a typical NP-hard problem,this problem has some disadvantages,such as difficult to solve and slow to solve.In order to solve this problem,this paper proposes two different optimization algorithms,which are respectively used to solve single-objective and multi-objective problems,and tests them on simulation examples Brandimarte,Barnes and real examples,and compares them with other algorithms.The main research work and related results are as follows:1.Summarize the research background,history,current situation of the FJSP,and the solution of the FJSP,including accurate algorithms and approximate algorithms.The accuracy of accurate algorithm is very high,but takes a long time to solve,and the solution may not be successful.The accuracy of approximate algorithm has lower accuracy than that of accurate algorithm,but a shorter time,and each problem can get the optimal solution or approximate optimal solution.In the meanwhile,the approximate solution method is most widely used in current research.In this paper,the FJSP has been built,in which the industrial problem is transformed into mathematical problem,and the basic model and two common algorithms(genetical gorithm,GA,and particle swarm optimizational gorithm,PSO)are proposed.The two common algorithms are improved to obtain applicable methods,which are mostly used to solve the problem at present.2.The goal of FJSP is to minimize the maximum completion time,and the IPSO-NSGA-Ⅱ algorithm is proposed to solve the mininization problem.For the inertia factor in the particle swarm optimization algorithm,the adaptive adjustment strategy is adopted in solving the problem.In NSGA-Ⅱ algorithm,different crossover methods are used for process and machine,and different mutation methods are also used for process and machine,so as to increase the diversity of solutions.For the global search ability of NSGA-Ⅱ algorithm to the problem,the IPSO and NSGA-Ⅱ are combined by hierarchical technology,which makes it more applicable to the global optimal solution of the problem.The experiments showed that this method is not weaker than other algorithms.3.The optimization problem is taken as a set of the maximum completion time,machine load and energy consumption of FJSP.Greedy-NSGA-Ⅱ algorithm is used to to find a better method for the Pareto optimal solution by changing the processes.It is shown that this method is not weaker than other algorithms.The two optimization algorithms have laid a good foundation for solving the other problems of FJSP.