Study on Design Task Programming Method Based on Simulation Optimization Algorithm

摘要：

Aiming at shortcomings of existed design structure matrix based task programming methods, a new stochastic task programming model is built in which task execution time and cost are described as stochastic variable subjected to some type of probability distribution. In view of built task programming model, a hybrid simulation optimization algorithm is developed which adopts ordinal optimization and optimal computing budget allocation technique based genetic algorithm to perform local search in the framework of nested partitions method. Hybrid algorithm unites various advantages of genetic algorithm in powerful local search and nested partitions in global optimization. A task programming case study of rotor and bearing system validates that our task programming model and solving algorithm are efficient and effective.

关键词： task programming design structure matrix simulation optimization nested partitions ordinal optimization

作者: Yan Lijun Li Zongbin Yuan Xiaoyang

作者单位: Xian Jiaotong University, Xian, Shaanxi, 710049, China

会议类型: 国际会议

会议名称: 2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

会议地点: 长沙

会议语种:英文

页码: 2855-2858

在线出版日期: 2010-05-11（万方平台首次上网日期，不代表论文的发表时间）