Solving a Class of Job-Shop Scheduling Problem based on Improved BPSO Algorithm
基于改进BPSO算法求解一类作业车间调度问题

Analyzing the special job shop scheduling problem of a large-scale machine shop,considering workers' operational qualification and characteristics of discretely concurrent production,a novel mathematical model has been proposed to meet actual production.In addition,an improved Binary Particle Swarm Optimizer(BPSO) algorithm has been developed for solving the problem how to arrange m workers to process n structures,in order to optimize the minimum completion time of the jobs.In this improved BPSO,a new method of making initial particles has been presented for searching optimum particle in the feasible dimensional problem space.Besides,importing memory base,modifying Sig function and considering constraint condition have used in algorithm for making updated particles to meet the constraint equation of mathematical model.Algorithm examples research demonstrates that the improved BPSO algorithm is effective and can achieve good results.Moreover,the mathematical model has wide application in discrete manufacture.