改进GSA算法在协同制造任务分配中的应用

摘要

To solve the collaborative manufacturing task assignment problem, a multi-objective optimization model is developed to minimize the task time,cost and maximize the machining quality. In order to simplify the problem,the multiple objectives problem is converted into the single objective problem using the classical weighting algorithm. FAHP is adopted to establish a fuzzy analytical hierarchy model for the collaborative manufacturing task assignment problem to satisfy different users' request,and then the weights of each objective are obtained. Based on the model,a modified genetic simulated annealing algorithm is designed to solve the model.Finally,an example is given to prove the model and algorithm to be efficient.%针对网络化协同制造中的任务分配问题,建立了以制造任务完成时间、完成成本、产品工艺质量为目标的多目标优化模型,提出了模型求解的改进遗传模拟退火(Genetic Simulated Annealing,GSA)算法.建立了协同制造任务分配的层次结构模型,应用模糊层次分析法分析了时间、成本和工艺质量等因素在协同制造任务分配过程中的相对重要性.设计了优化模型求解的改进遗传模拟退火算法,并结合具体实例验证了算法的有效性和优越性.