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新型遗传算法求解车辆路径问题研究
引用本文:张瑞锋,汪同三. 新型遗传算法求解车辆路径问题研究[J]. 湖北大学学报(自然科学版), 2012, 34(2): 239-242
作者姓名:张瑞锋  汪同三
作者单位:中国社会科学院数量经济与技术经济研究所,北京,100732
摘    要:建立有时间窗车辆路径问题的数学模型,针对遗传算法在局部搜索能力方面的不足,提出将模拟退火算法与遗传算法相结合,从而构造有时问窗车辆路径问题的混合遗传算法,并进行实验计算.结果表明,用混合遗传算法求解该优化问题,可以在一定程度上克服遗传算法在局部搜索能力方面的不足和模拟退火算法在全局搜索能力方面的不足,从而得到质量较高的解.

关 键 词:车辆路径问题  时间窗  遗传算法  模拟退火算法

New genetic algorithm for vehicle routing problem
ZHANG Ruifeng , WANG Tongsan. New genetic algorithm for vehicle routing problem[J]. Journal of Hubei University(Natural Science Edition), 2012, 34(2): 239-242
Authors:ZHANG Ruifeng    WANG Tongsan
Affiliation:(Institute of Quantitative & Technical Economics,Chinese Academy of Social Sciences, Beijing 100732,China)
Abstract:We stated a universal mathematical model of vehicle routing problem with time windows.On the basis of analyzing the weakness of genetic algorithm in local search,a new stochastic approach called the genetic simulated annealing algorithm was proposed to solve vehicle routing problem with time windows,and made some experimental computations.The computational results demonstrated that the genetic simulated annealing a80lgorithm could overcome the weakness of genetic algorithm and local search algorithm,and the high quality solutions of the vehicle routing problem with time windows was obtained.
Keywords:vehicle routing problem  time window  genetic algorithm  simulated annealing
本文献已被 CNKI 维普 万方数据 等数据库收录!
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