摘要
工作流优化有多种不同的手段,按照优化操作的对象不同,可以分为结构优化和参数优化。资源优化是工作流参数优化领域的热点,优化资源数量可以最大化地改善工作流时间性能。优化算法主要涉及遗传算法、基于Petri网结构的并行优化和与扩展Petri网结合的遗传算法等。工作流验证目的是在过程设计时检验工作流的正确性,避免执行时出现异常。在工作流模型实际实施之前,探测其中可能存在的各种过程异常可以降低工作流运行时的停产、检查和修复的成本,具有重大的经济意义。车间作业调度问题是一类最具一般性的生产调度问题,采用这种新型的扩展Petri网对调度问题进行建模,结合遗传算法对该调度问题进行优化,最后得到了问题的最优解。这种基于扩展Petri网的遗传算法具有较高的通用性。
Workflow optimization includes a number of different means. According to the optimization of operating at different targets, workflow optimization consists of structural optimization and quantitative optimization. Resource optimization is a hot spot in the field of the workflow optimization and optimizing the amount of resources can maximize the flow of time so as to improve performance. Optimization related to mainly genetic algorithms, parallel structural optimization with Petri net, and the genetic algorithm based on extended Petri nets （EPN） etc. The workflow verification is mainly testing of the accuracy in the process of designing workflow and it can avoid unusual. Before the workflow model being used in the actual implementation, the verification could detect the abnormal existence, therefore the process be able to reduce the abnormal flow of the cut - off operation, inspection and repair costs, so it is of great economic significance. Job-Shop scheduling problem is the most general of the scheduling problem, the new type of extended Petri nets to model for the scheduling problem, combined with genetic algorithm to optimize the scheduling problem and finally got the optimal solution. The genetic algorithm based expansion Petri net has higher universality than others.
出处
《计算机技术与发展》
2009年第6期156-159,共4页
Computer Technology and Development
基金
内蒙古自然科学基金资助项目(200607010810)
