首页> 外文期刊>Journal of modelling in management >Genetic scatter search algorithm to solve the one-commodity pickup and delivery vehicle routing problem
【24h】

Genetic scatter search algorithm to solve the one-commodity pickup and delivery vehicle routing problem

机译:遗传散点搜索算法解决一站式取货车运输路线问题

获取原文
获取原文并翻译 | 示例
       

摘要

Purpose - In this paper, the author introduces a new variant of the pickup and delivery transportation problem, where one commodity is collected from many pickup locations to be delivered to many delivery locations within pre-specified time windows (one-to many-to many). The author denotes to this new variant as the 1-commodity pickup-and-delivery vehicle routing problem with soft time windows (1-PDVRPTW). Design/methodology/approach - The author proposes a hybrid genetic algorithm and a scatter search to solve the 1-PDVRPTW. It proposes a new constructive heuristic to generate the initial population solution and a scatter search (SS) after the crossover and mutation operators as a local search. The hybrid genetic scatter search replaces two steps in SS with crossover and mutation, respectively. Findings - So, the author proposes a greedy local search algorithm as a metaheuristic to solve the 1-PDVRPTW. Then, the author proposes to hybridize the metaheuristic to solve this variant and to make a good comparison with solutions presented in the literature. Originality/value - The author considers that this is the first application in one commodity. The solution methodology based on scatter search method combines a set of diverse and high-quality candidate solutions by considering the weights and constraints of each solution.
机译:目的-在本文中,作者介绍了提货和送货运输问题的新变体,其中从许多提货地点收集一种商品,然后在预定的时间范围内(一对多对多)。作者将此新变量表示为带有软时间窗(1-PDVRPTW)的1-商品取送车辆路径问题。设计/方法/方法-作者提出了一种混合遗传算法和一种分散搜索来解决1-PDVRPTW。它提出了一种新的建设性启发式方法,以生成初始总体解,并在交叉和变异算子之后将散点搜索(SS)作为局部搜索。混合遗传散点搜索分别用交叉和突变取代了SS中的两个步骤。结果-因此,作者提出了一种贪婪的局部搜索算法作为元启发式算法来解决1-PDVRPTW问题。然后,作者提出将元启发式算法混合以解决该变体,并与文献中提出的解决方案进行很好的比较。原创性/价值-作者认为这是一种商品中的首次应用。基于散布搜索方法的解决方案方法通过考虑每个解决方案的权重和约束条件,结合了一组多样化且高质量的候选解决方案。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号