摘要
针对一类不确定需求和旅行时间下的随机车辆路径问题,建立了一个随机规划模型,提出了一种带有自适应机制的改进遗传算法。该算法引入自适应选择机制,采用了新的交叉算子。选取两种不同规模的随机车辆调度问题,分别采用该算法和基于边重组的改进遗传算法进行求解,并通过对计算结果进行对比分析,分别针对自适应选择机制和新的交叉算子做了讨论。结果表明,所提算法不仅取得了更好的优化结果,而且具有更快的收敛速度。
To study stochastic Vehicle Routing Problems（VRP） with uncertain demand and travel time,a stochastic programming model was formulated and an improved genetic algorithm with self-adaptive mechanism was proposed for routes optimization.Self-adaptive selection mechanism was introduced for amending the fitness value to overcome the premature convergence effectively and a new crossover operator was developed in the algorithm.Computational simulations and comparisons based on two kinds of stochastic VRP problems with different size were provided.Results demonstrated that the proposed algorithm obtained better results with higher convergence speed.
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2011年第1期101-108,共8页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(70771003
70821061)~~
关键词
随机需求
随机旅行时间
随机规划模型
车辆路径问题
遗传算法
自适应机制
stochastic demand
stochastic travel time
stochastic programming model
vehicle routing problem
genetic algorithms
self-adaptive mechanism
