Stochastic Vehicle Routing Problems and their Solution Algorithm

被引：0
|
作者：
Wang Dedong [1 ]
Chen Qijun [1 ]
Li-li [2 ]
机构：
[1] Univ Shandong Jianzhu, Dept Engn Management, Jinan 250101, Shandong, Peoples R China
[2] Shandong Univ, Dept Mech & Elect Engn, Jinan, Peoples R China
来源：
2008 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6 | 2008年
关键词：
vehicle routing problem; simulated annealing; genetic algorithm; optimization; supply chains;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The standard simulated algorithm has been applied into vehicle routing problem, and it has the common defects of slow convergence and easily being trapped into local minima. In this paper, a new stochastic approach called the simulated annealing genetic algorithm is proposed to solve stochastic vehicle routing problems and the solution is then compared with that from simulated algorithm. Results from case studies show that the proposed algorithm can avoid getting stuck in local minima and has better convergence property and find the optimal or near-optimal solution effectively as well as time and quickly convergence property. So, it is an efficient method for vehicle routing problem.
引用
收藏
页码：958 / +
页数：2
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