摘要
分析了车辆路径问题的研究方法和遗传算法的特点,提出了一种改进的遗传算法求解车辆路径问题.在算法的求解过程中,构造了一种新的编码方式,能够显著减少编码长度.通过保留每代最佳的若干染色体以及引入期望繁殖率的概念,本算法可以实现解的多样性,避免收敛于局部最优解,同时可以有效的防止在进化的过程中失去最优解的可能性.实验结果表明,本算法可以快速求得优化解,是求解车辆路径问题的一种有效算法.
Analyzes the research approaches of vehicle routing problems and characteristics of genetic algorithm, and proposes an improved genetic algorithm for the vehicle routing problem. A kind of new coding manner is constructed which can improveto run efficiency of algorithm on the basis of reducing coding length. The algorithm can implement the diversity of solution, avoid converging local optimal solution, and prevent the possibility of losing optimal solution effectively, by holding some optimal chromosomes in each generation and introducing expectation reproduction rate. Experiment results indicate the algorithm can converge the optimal solution rapidly and is an effective algorithm.
出处
《天津理工大学学报》
2006年第5期79-82,共4页
Journal of Tianjin University of Technology
关键词
车辆路径
遗传算法
物流配送
优化
vehicle routing
genetic algorithm
logistics distribution
optimization
