Study on Vehicle Routing and Scheduling Problems in Underground Mine Based on Adaptively ACA

摘要：

For vehicle routing optimization problem in the underground mine, a famous NP- Hard problem is put forward. This paper uses improved ant colony algorithm (ACA) to solve the problem. Basic ant colony algorithm (ACA) has many shortages, such as long searching time, slow convergence rate and easily limited to local optimal solution etc. The improved ant colony algorithm is proposed to overcome these shortcomings and improve its performance adaptively. In every iteration of the ant colony algorithm, adaptive evaporating coefficient is selected to control the convergence rate at first. And the power of this approach was demonstrated on a test case. The results derived from basic ACA and the improved ACA are compared and analyzed in the experiment. It proved that the improved ant colony algorithm is effective.

关键词： Improved ACA vehicle routing problem pheromone tunnel

作者: Gu Qinghua Jing Shigun

作者单位: School of Management, Xian University of Architecture STechnology, Xian, China

会议类型: 国际会议

会议名称: 2011 International Conference on Mechatronics and Applied Mechanics(2011年机电一体化与应用力学国际会议 ICMAM 2011)

会议地点: 香港

会议语种:英文

页码: 1293-1296

在线出版日期: 2011-12-27（万方平台首次上网日期，不代表论文的发表时间）