基于仿真的生产调度优化技术研究

现有的调度方法无法同时达到既能建立精确的调度模型又能获得满意的调度结果.为此,提出了基于仿真的优化调度方法.该方法包括试验设计模块、遗传算法模块和仿真模型.首先由试验设计模块设计遗传算法的参数值的组合方案,然后由遗传算法采用每组参数值与仿真模型进行反复迭代,筛选出一组最佳的调度规则序列,以及与其对应的生产系统性能指标值.将该性能指标值反馈到试验设计模块,并选择下一组方案重新进行上述过程.当所有方案试验完毕后,对试验结果进行分析,确定最佳的遗传算法参数值组合方案,以及与该方案对应的调度结果.最后,以某研究所机加车间为例,验证了该方法的可行性和有效性.

Production optimal scheduling technology based on simulation

Current scheduling approach cannot construct a precise scheduling model and obtain satisfactory scheduling result at the same time.To deal with this problem,an optimal scheduling approach based on simulation optimization methodology was presented which was composed of three basic modules: experiment design module,Genetic Algorithm(GA) module and simulation model.Firstly,a combinatorial plan of parameter values for GA was designed by the orthogonal test.Then,a set of optimal scheduling rule sequence was obtained by repeated iteration of each parameter value and simulation model,therefore the corresponding performance index value of the production system was also obtained.The performance index value was returned to experiment design module and next set of plan was selected to conduct repeated iteration.The best combinatorial parameter value for GA and the optimal scheduling result were defined after completing all experiments and comparing test results.Validity and feasibility of this approach were proved by a case study in the workshop of a research institution.