A Hybrid Ant Colony Optimization and Its Application to Vehicle Routing Problem with Time Windows

摘要：

The Ant Colony Optimization (ACO) is a recent metaheuristic algorithm for solving hard combinatorial optimization problems. The algorithm, however, has the weaknesses of premature convergence and low search speed, which greatly hinder its application. In order to improve the performance of the algorithm, a hybrid ant colony optimization (HACO) is presented by adjusting pheromone approach, introducing a disaster operator, and combining the ACO with the saving algorithm and λ-interchange mechanism. Then, the HACO is applied to solve the vehicle routing problem with time windows. By comparing the computational results with the previous literature, it is concluded that the HACO is an effective way to solve combinatorial optimization problems.

关键词： Ant Colony Optimization Vehicle Routing Problem with Time Windows Combinatorial Optimization Problems

作者: Xiangpei Hu Qiulei Ding Yunzeng Wang

作者单位: Institute of Systems Engineering, Dalian University of Technology,Dalian, China, 116023 A.Gary Anderson Graduate School of Management, University of California,Riverside, California, USA,

会议类型: 国际会议

会议名称: International Conference on Life System Modeling and Simulation,and International Conference on Intelligent Computing for Sustainable Energy and Environment(2010生命系统建模与仿真国际会议暨m2010可持续能源与环境智能计算国际会议)

会议地点: 无锡

会议语种:英文

页码: 70-76

在线出版日期: 2010-09-17（万方平台首次上网日期，不代表论文的发表时间）