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Research on Vehicle Routing Problem with Soft Time Windows Based on Hybrid Tabu Search and Scatter Search Algorithm

机译:基于混合动力禁忌搜索和分散搜索算法的软时间窗口车辆路由问题研究

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摘要

With the expansion of the application scope of social computing problems, many path problems in real life have evolved from pure path optimization problems to social computing problems that take into account various social attributes, cultures, and the emotional needs of customers. The actual soft time window vehicle routing problem, speeding up the response of customer needs, improving distribution efficiency, and reducing operating costs is the focus of current social computing problems. Therefore, designing fast and effective algorithms to solve this problem has certain theoretical and practical significance. In this paper, considering the time delay problem of customer demand, the compensation problem is given, and the mathematical model of vehicle path problem with soft time window is given. This paper proposes a hybrid tabu search (TS) & scatter search (SS) algorithm for vehicle routing problem with soft time windows (VRPSTW), which mainly embeds the TS dynamic tabu mechanism into the SS algorithm framework. TS uses the scattering of SS to avoid the dependence on the quality of the initial solution, and SS uses the climbing ability of TS improves the ability of optimizing, so that the quality of search for the optimal solution can be significantly improved. The hybrid algorithm is still based on the basic framework of SS. In particular, TS is mainly used for solution improvement and combination to generate new solutions. In the solution process, both the quality and the dispersion of the solution are considered. A simulation experiments verify the influence of the number of vehicles and maximum value of tabu length on solution, parameters' control over the degree of convergence, and the influence of the number of diverse solutions on algorithm performance. Based on the determined parameters, simulation experiment is carried out in this paper to further prove the algorithm feasibility and effectiveness. The results of this paper provide further ideas for solving vehicle routing problems with time windows and improving the efficiency of vehicle routing problems and have strong applicability.
机译:随着社会计算问题的应用范围的扩展,现实生活中的许多路径问题已经从纯粹的路径优化问题演变为社会计算问题,考虑到各种社会属性,文化和客户的情感需求。实际的软时间窗车路由问题,加快客户需求的响应,提高分配效率,降低运营成本是当前社会计算问题的重点。因此,设计快速和有效的算法来解决这个问题具有某种理论和实际意义。在本文中,考虑到客户需求的时间延迟问题,给出了补偿问题,给出了软时间窗口的车道问题的数学模型。本文提出了一种具有软时间窗口(VRPSTW)的车辆路由问题的混合禁忌搜索(TS)和散点搜索(SS)算法,其主要将TS动态禁忌机制嵌入到SS算法框架中。 TS使用SS的散射来避免对初始解决方案的质量的依赖性,并且SS使用TS的攀爬能力提高了优化的能力,从而可以显着提高最佳解决方案的质量。混合算法仍然基于SS的基本框架。特别是,TS主要用于解决方案改善和组合以产生新的解决方案。在解决方案过程中,考虑质量和溶液的分散。仿真实验验证了禁忌长度对解决方案的数量和最大值的影响,参数对收敛程度的控制,以及各种解决方案数量对算法性能的影响。基于所确定的参数,在本文中进行了仿真实验,进一步证明了算法可行性和有效性。本文的结果提供了解决车辆路由问题的进一步思想,随着时间窗口,提高车辆路径问题的效率,具有很强的适用性。

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