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Research And Application On Job Shop Scheduling Method Based On Hybrid Genetic Algorithm

Posted on:2007-05-14Degree:MasterType:Thesis
Country:ChinaCandidate:S B DingFull Text:PDF
GTID:2132360212957576Subject:Mechanical and electrical engineering
Abstract/Summary:PDF Full Text Request
Nowadays, the cycles of production development and handover are shortened largely with the development of the economy. Multi-categories, small batch and customization manufacturing mode has become the mainstream of the machine production. This mode makes production planning and resource assignments more complicated. Correlative data indicates that 95 percent of the production time is not used for cutting. In the competition environment of time is profit, how to use the computer technology to realize the production scheduling optimization, to adjust resource assignments quickly and to plan production with due consideration for all concerned has become a great subject for many manufactory.In this paper, typical jop shop scheduling problem (JSP) is researched. Based on the good characteristics of genetic algorithm(GA)and simulated annealing (SA)in achieving near optional solution of this problem, a hybrid algorithm of genetic and simulated annealing (GASA) is proposed for the solution of job shop scheduling, and a new encoding method is presented for this hybrid algorithm, the corresponding decode method is established also. Meanwhile, the methods of getting the initial temperature and the fitness function are discussed. The simulation of the LA16 scheduling problem shows the feasibilities and availabilities of GAGA, and the simulated results based on GASA, SA and GA show that this hybrid genetic algorithm can improve on the deficiencies of genetic algorithm and simulated annealing in the optimization on JSP.Meanwhile, Flexible job shop scheduling problem (FJSP) with Multi-categories, small batch and customization is investigated, corresponding mathematics model is constructed, and a new encoding method and corresponding decoding method for FJSP are designed, the use of GASA in FJSP is researched in detail. A rescheduling strategy is proposed for the dynamic scheduling of FJSP. One instance indicates that the algorithm is effective.Finally, the design and realization of the job shop scheduling system based on GASA are expounded, the functions and operations of the system modules are introduced detailedly. The scheduling result satisfies the requirements, which shows the availabilities of GASA further.
Keywords/Search Tags:Genetic Algorithm, Simulated Annealing, Job Shop Scheduling, Flexible Job Shop Scheduling
PDF Full Text Request
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