Integrated Optimization Of Process Planning And Job Shop Scheduling Based On Multi-objective Fruit Fly Optimization Algorithm

With the rapid development of the global economy,the manufacturing industry has also entered a new period of development,followed by increasingly fierce market competition among enterprises.As two very important parts of the manufacturing system,process planning and job shop scheduling directly restrict the production capacity of the entire manufacturing system and the effective utilization of resources.Due to the continuous improvement of customers’ individual needs,the production method of "diversified types and smaller production batches" is used by more and more manufacturing enterprises.In the face of this dynamic market demand,the effective integration of the process planning system and the job shop scheduling system has become more and more important.This article will conduct research on the integration strategy of these two key links and the corresponding algorithm design.This paper proposes a research method for flexible process planning based on fruit fly optimization algorithm.In response to this problem,a three-part coding method is designed to deal with processing process flexibility,processing sequence flexibility and processing machine flexibility.The olfactory search stage of the fruit fly optimization algorithm is improved.Three operations of insertion,exchange,and mutation are used to construct neighborhoods,and a global collaboration mechanism is introduced to enhance the collaboration between populations,thereby improving the performance of the algorithm.An example is used to verify the effectiveness of the fruit fly optimization algorithm on this problem,which lays a foundation for the research on the integrated optimization problem of process planning and job shop scheduling.Based on the research of flexible process planning,an integrated optimization method of process planning and job shop scheduling based on multi-objective fruit fly optimization algorithm is proposed.This paper takes minimizing the maximumcompletion time,minimizing the maximum machine load and minimizing the total processing cost as the research goals,and combines the Pareto method with the fruit fly optimization algorithm according to the multi-objective characteristics,and proposes a multi-objective fruit fly optimization algorithm based on the Pareto method.In the olfactory search stage,the neighborhood is generated by inserting.In order to solve the problem of individual update in the visual search stage,the method of comparing the degree of dissimilarity is used to replace the individual of the parent fruit fly.In the global collaboration stage,the POX crossover method is used for global collaboration.In order to improve the quality of Pareto solution set,the method of calculating the congestion distance is used to update and maintain the non-inferior solutions in the external files.According to the proposed research results,numerical examples are verified,and the effectiveness of the algorithm proposed in this paper is verified by comparison with various algorithms.And through the actual investigation of the manufacturing workshop of a reducer manufacturer,it was found that the manufacturing workshop of the company had problems such as long processing time and high total processing cost.The research results of this article are actually applied to this case,and good results are achieved.