Study On Multi-objective Flexible Job-shop Scheduling Problem

Our country formulated a series of industrial restructuring strategic decisions, Suchas the "promoting industrialization and informatization whit a sustained and healthydevelopment","actively adapt to the changing of domestic and international situations,accelerating the formation of a new mode of economic development, to promote theindustry through transformation and upgrading ". As it to improve industrialcompetitiveness, seek rapid economic development and powerful status, manufacturinginformation was an important way to achieve wealthy and powerful. The schedulingtechniques in manufacturing process is an important part of modern management. Aftermore than half a century of research, shop scheduling problem achieved fruitful resultsin theoretically. However, because there were many complex emergencies in the actualproduction process, many of the studies are based on a series of assumptions conditions.Modern study takes more actual production status into account, multi-objective flexiblejob shop scheduling problem not only combined the flexible characteristics of theproduction process, but also takes into account a number of scheduling performance ofthe production process, and it has more modern manufacturing significance. This paperusing the existed research results of the shop scheduling problem had a systematic studyto the theories and methods of multi-objective flexible job shop scheduling problem.The main results of the paper are as follows:(1)Based on research results of the classical job shop scheduling problem,established the model of multi-objective flexible job shop scheduling problem, whichcloser to the actual production situation production.(2)This paper improved the cuckoo search algorithm, and put the improvedalgorithm into the multi-objective flexible job-shop scheduling problem. Cuckoo searchalgorithm can take advantage of parallel computing, powerful and fast convergenceconditions, improved the cuckoo algorithm which was designed to solve themulti-objective flexible job-shop scheduling problem, and compared to thenondominated sorting genetic algorithm which had been a fruitful research in the multi-objective flexible job shop scheduling problem,it demonstrated the superiority.(3)Through specific examples simulation results show that the improved algorithmcould solve the general multi-objective flexible job shop scheduling problem feasibleand effective.