Optimization In Production Scheduling

Production scheduling exists everywhere in the real world, especially in the field of industry and engineering.The production scheduling problems put forward by manufacturing are essentially extraordinary complexity and these are difficult to solve by traditional optimized methods.The assignment of a sehedule is that according to produce goal and restriction to arrange the detailed process line, time, machine, and operation etc. So good schedule methods can enhance manufacture system optimization character and economy benefit.The mathematic programming method can only establish static mathematic model, it lacks timeliness and efficiency, the mathematical model cannot be reuse.This thesis has proposed a simulation way to solve this problem.Rely on simulation, the experiments which are controllable, low cost and can duplicate many times are possible.It is an effective integrated method, it is the strategic technology which can rapidly improve the production process.Firstly, this paper discussed the importance of production scheduling and the existent problems in this domain are analyzed; The basic theories about scheduling are studied.Secondly, the basic theories of genetic algorithms, including its basic concepts, operation, and flow chart etc, are studied.The thesis has improved upon the structure of GA aiming at the problem that GA is easy to run into local optima, appear premature convergence and has low probability of convergence after research and analysis.And the IGA, including dynamic self-adapting method, can search the global optimum rather than local optimum, and enhance the optimum rate based on fast searching rate.The thesis has solved FSP by different implementation methods of IGA and optimized the procedure. This algorithm has some better results by means of verifying the problem of locomotive model.Finally, the thesis achieved dynamic simulation of Flexsim on FSP.The whole scheduling process of dynamic simulation can be observed.The simulation has provided a test platform for production plan of the production workshop.