Research And Application Of Multi-objective Flexible Intelligent Scheduling Problem In Discrete Manufacturing Industry

The development of traditional job shop scheduling problem is multi-objective flexible shop scheduling,multi-objective flexible shop scheduling is more in line with the actual production of the workshop,the study of the problem has practical significance.This article relies on Ningxia a Instrument Manufacturing Co.,Ltd.as the background,the enterprise is a discrete manufacturing valve business,to achieve a multi-species,multi-batch,m-ulti-batch production in line with the modern market dynamics,production is usually subject to multiple aspects Of the factors.In the case of satisfying the customer's demand,we take three objective functions,which are the minimum objective load,the shortest processing time and the minimum cost,which are the three objective functions of the enterprise.If you want three goals to achieve the desired value of the enterprise profit,then you need a reasonable workshop sc-heduling model and effective production scheduling algorithm.Based on the comprehensive analysis of the problem of workshop scheduling at home and abroad,this paper makes a systematic study on the multi-objective job-shop scheduling problem considering the actual situation of the flexible operation workshop in this study.The main work of this paper is:(1)Starting from the shortcomings of the existing workshop scheduling model,this paper p-resents a hierarchical approach to object-oriented colored Petri net;the previous Petri net model can cause space explosion,no modularity and lack of Reusability,Petri net modeling in this p-aper through the layered thinking and object-oriented technology can overcome these shortcomi-ngs.(2)Aiming at the problem of shop scheduling in a certain enterprise in Ningxia,an ant co-lony particle group hybrid workshop scheduling algorithm is proposed.Because the particle sw-arm algorithm is characterized by the iterative speed is very fast and easy to oscillate near the optimal solution.The ant colony algorithm is characterized by the lack of initial pheromone,the use of ant colony particle swarm optimization algorithm to solve the workshop scheduling The Firstly,the coding and decoding of the algorithm and the normalization of the target are intro-duced.Then,the flow chart of the two algorithms is given.Finally,the flow chart is introduced in detail.(3)Combine two groups of ant colony particle groups to solve the multi-objective flexible shop scheduling in actual production.Through the analysis of the non-inferior solution and the Gantt chart in the experimental results of the particle swarm optimization algorithm and the t-wo hybrid algorithms,it is found that the hybrid algorithm is more effective.