Research On Job-shop Scheduling Method Based On Particle Swarm Optimization

Job-shop Scheduling Problem is a NP problem. In order to study on it effectively, firstly, a Job-shop Scheduling Method Based on Particle Swarm Optimization is advanced in this dissertation after analyzing the problem's research content, evaluative criterions, problem characteristics and conventional algorithms. Secondly, on the base of analyzing the Particle Swarm Optimization (PSO) basic theory, algorithm characteristics and application fields, a standard PSO algorithm is advanced by the optimization target of minimum make-span time and the work procedure coding method, and this algorithm can be used to optimize the Job-shop Scheduling Problem, and then the astringency of the algorithm is proved through an application instance. At last, because the standard PSO algorithm can't optimize the complex Job-shop Scheduling problem, combining standard PSO algorithm with genetic algorithms and simulated annealing algorithms, a hybrid-PSO algorithm is put forward, and then the astringency of the algorithm is proved by optimizing a complex Job-shop Scheduling problem instance.