首页> 外文会议>Intelligent Information Systems, 1997. IIS '97. Proceedings >A heuristic modification of genetic algorithm used for solving the single depot capacited vehicle routing problem
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A heuristic modification of genetic algorithm used for solving the single depot capacited vehicle routing problem

机译:遗传算法的启发式修改,用于解决单基地车辆停运的车辆路径问题

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The paper proposes a genetic algorithm (GA) in conjunction with handy heuristic techniques to solve the single depot capacited vehicle routing problem (CVRP). The genetic algorithm is developed on the basis of experiences in solving the travelling salesman problem (TSP). Few heuristic improvements are added in order to prevent converging to local optima and to reduce the search space domain. To deal effectively with constraints of the problem and prune the search space of the GA in advance, the constraints are embedded in decimal coding of the problem. The proposed GA approach has been tested on several CVRP with different number of consumer nodes and different control parameters. The results of 144 node problem used for sensitivity analysis, reveal that the features of easy implementation, fast convergence, and near optimal solution in solving the CVRP can be achieved by the proposed GA approach.
机译:本文提出了一种遗传算法(GA)与方便的启发式技术结合,以解决单个仓库电容车辆路由问题(CVRP)。遗传算法是在解决旅行推销员问题(TSP)的经验的基础上开发的。添加了很少的启发式改进,以防止会聚到本地Optima并减少搜索空间域。为了有效处理问题的限制并提前修剪GA的搜索空间,约束嵌入了问题的十进制编码中。已经在几个CVRP上测试了所提出的GA方法,具有不同数量的消费节点和不同的控制参数。 144节点问题用于灵敏度分析的节点问题,揭示了易于实现,快速收敛性和求解CVRP的最佳解决方案的特征可以通过所提出的GA方法实现。

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