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Improved Genetic Algorithm And Simulated Annealing In Mould Manufacturing Job-shop Scheduling Of Studies

Posted on:2011-05-25Degree:MasterType:Thesis
Country:ChinaCandidate:H WangFull Text:PDF
GTID:2132330332483494Subject:Computer application technology
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Job-shop scheduling problem belongs to the typical scheduling problem, workshop scheduling problem is talking about the certain time constraint condition, how to dispatch the workshop limited resources, perform task, while also satisfy certain constraints. Resources, including different kinds, human, cash, equipment, electrical energy, raw materials, etc. Task also includes different elements, completion time, delivery time, critical degree, human consumption and resource consumption, etc. At the same time between tasks have order constraint, etc. Workshop scheduling problem in today's manufacturing enterprise is widely used, many practice need to implement a scheduling problem in essence are very complex and by traditional combinatorial optimization method difficult to achieve. All these problems is NP difficult problem.-Genetic algorithm and simulated annealing algorithm to solve the problems when have more thorough research and application, so use genetic algorithm and simulated annealing algorithm to solve the scheduling problems become a research direction.Job-shop scheduling problem is given a homework set and a machine equipment set. Every machine at the same time can processing a homework, but each assignments include a series of working procedure, each working procedure in some machines need continuous processing some time. Workshop scheduling research task in complete problem is how to make the time needed for the shortest of. In the past few decades, many domestic researchers of this problem is studied, and that many encouraging results. But as the workshop scheduling problem need to consider the actual problem more and more complex, unexpected situation more and more, at the same time for scheduling real-time and effectiveness of the demand is higher and higher, enterprises need more suitable for this enterprise's workshop scheduling solution to appear.Based on extensive reading of documents, on the basis of predecessors' obtains the research achievements on reanalysis, especially to the simulated annealing algorithm and genetic algorithm carry on comprehensive research, the improved genetic simulated annealing algorithm. Through actual data validation, this algorithm reduces the genetic algorithm in local precocious probability of this algorithm is improved search efficiency, can add to the actual workshop scheduling problem plays a certain improvement action. Meanwhile, according to some mould manufacturing company's actual situation, we designed and developed a set of against the company mold manufacture workshop scheduling system, this system to optimize and improve the workshop scheduling problem feasible.
Keywords/Search Tags:Genetic algorithm, Simulated annealing, Adaptive operators, production scheduling
PDF Full Text Request
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