Study Of The Dynamic Orders Scheduling Based On Mixed-ga

With orders scheduling and inserting adopted by production-line plants as the objects of the study, the problems of orders sorting and production arrangement are studied to discuss how to distribute orders to assembly-line to realize production allocation optimization. Two models of orders scheduling are established with objects of min resources consuming and the most balanced resources allocation, strategy of mixed-genetic algorithms is designed through MATLAB7.0 to solve the models to find the best way of production scheduling, combined with production scheduling problem of SMT production line in an electronic factory in Shenzhen, for the purpose of shortening delivery time, and improving utility of production line, and enhancing the competition ability.Chapter one analyzes and discusses the characters of the three processes during scheduling in production-line factories, and studies the situations about the scheduling both in domestic and abroad. The meaning, purpose and structure of this paper are elucidated on the foundation of aspects discussed above.Chapter two mainly researches orders selecting in the first process of the scheduling, and orders inserting in the second one. The method of orders priority ranking which based on AHP is put forward after analyzing and establishing the procedure of orders scheduling and orders inserting.Chapter three, the most important part in this paper, introduces order scheduling, which is also the third step of the scheduling process, and establishes GAP and BAP models about production line order scheduling.The procedure of Genetic Algorithms (GA) and Tabu Search (TS) is analyzed in chapter four, and the advantages and drawbacks of the two methods are discussed. GAP and BAP models established in chapter three can be solved by mixed-genetic algorithms designed in this chapter.In chapter five, the best scheduling method is supposed to be acquiring through mixed-genetic algorithms, combined with operation scheduling of SMT in a factory in Shenzhen, using MATLAB7.0 as the program researching and developing platform.The last chapter summarized the achievement and shortcomings of the paper; the future research work is also suggested.