A Multi-Agent Based Method For Job-Shop Scheduling Problem

With the development of information technology,the large-scale information manufacture systems become the current hot spot,because the old productive mode hasn't adapted to the requirement of modern advanced manufacture.As an important part of the manufacturing system,the job-shop scheduler affects the agility and intelligence of the whole enterprise.The research and application of Job-shop Scheduling method and optimizing technology is the key to realize advanced manufacture and improve the job-shop production efficiency.Since the Agent paradigm has many excellent characteristics,such as intelligence,autonomy and cooperation,etc.,Multi-Agent system provides a new efficient solution to Job-Shop scheduling of modern manufacturing system.The importance of this paper is to be attended to the Job-Shop scheduling model and scheduling arithmetic basing on Multi-Agent.According to found a manufacturing Job-Shop scheduling model,it proposes the scheduling mechanism and strategy integrating Multi-Agent and hybrid genetic algorithm,which are validated with the ILOG.Firstly,a Multi-Agent based manufacturing Job-Shop scheduling system architecture model is established.The model consists of four primary components: Manager Agent,Task Agent,Resource Agent and Cooperation Agent.In the basis of analyzing the advantages and disadvantages of agent architecture,the hybrid agent framework is established.Besides,to meet the needs of agent autonomous decision and interaction,the internal architecture model of various agent classes is designed and established.And it proposes the scheduling mechanism and strategy.Secondly,the paper analyzes the actuality of JSSP optimized methods and sums up their applied localization.Based on the good characteristics of genetic algorithm(GA) and simulated annealing algorithm(SA) in achieving near optional solution of this problem,a hybrid genetic algorithm(GASA) which combines GA and SA is proposed for the solution of JSSP.The GASA with the advantage of GA's whole searching and SA's local searching can increase the diversity of individuals in population and robust of algorithm.And the detailed designing process with GASA is worked over.Finally.the application of GASA is researched with ILOG and Visual Studio.net 2005.By testing typical instances,the results show the new algorithm is satisfactory.GASA is applied into a real-world scheduling system of a manufacturing enterprise in Deyang City to settle a simplified example.The result of this example is almost perfect and quickly.