Prior Optimization of Vehicle Routing Problem with Fuzzy demands
Owing to complexity of human cognition and uncertainty of linguistic description, fuzzy factors, in particular fuzzy demands often emerge in the course of route planning. To avoid disadvantages of re-optimization in computational complexity, two prior policies, TSP policy and MTSP policy are provided to solve vehicle routing problem with fuzzy demands. To evaluate effeciency of TSP policy and MTSP policy, the upper bounds, lower bounds and asymptotic properties of the policies are analyzed respectively. In view of successful experience in combinatorial optimization, genetic algorithms are applied to find the satisfying prior solutions.
Shi An Binglei Xie
School of Science and Engineering on Communication Harbin Institute of Technology Harbin, 150001 Shenzhen Graduate School Harbin Institute of Technology Shenzhen, 518055
国际会议
青岛
英文
2006-07-21（万方平台首次上网日期，不代表论文的发表时间）