An Efficient Algorithm Applied to Capacitated Vehicle Routing Problem with Consideration of Time Windows by Using Ranking-Based Concept and Dynamic Programming

Cheng Heng Uy, Nattanee Charoenlarpkul, T. Sarttra, S. Rajsiri
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引用次数: 2

Abstract

Capacitated Vehicle Routing Problem and Time-Windows (CVRPTW) is one of the most well-known variations of Vehicle routing problems (VRP), which is a combinatorial optimization and can be classified as NP-hard problem. A considerable number of solving techniques have been proposed not only exact and heuristic, but also metaheuristic methods. Although the optimal solution can be guaranteed applying the exact algorithms, computational time is the most concern when the problem size is increased. Heuristic methods normally provide solutions with a very fast speed but most of them are local optima. Metaheuristic methods are also other approaches to solve this problem providing much larger search space. However, most of them are on the basis of experiments requiring an extensive number of parameter settings. In this research, a novel efficient approach to solve CVRPTW is proposed using the several concepts of graph traversal with breadth-first search and ranking-based algorithm during the initial route construction, and Dynamic programming is then used for solution improvement with regarding to capacity constraints and time windows. The performance of the proposed method compared to the state-of-the-art algorithms will be very competent in terms of both solution quality and computational time with no effort on parameter settings as a major advantage.
基于排序和动态规划的考虑时间窗的有能力车辆路径问题的高效算法
有能力车辆路径问题和时间窗(Capacitated Vehicle Routing Problem and time - window,简称CVRPTW)是车辆路径问题(Vehicle Routing Problem,简称VRP)最著名的变体之一,它是一个组合优化问题,可归类为np困难问题。人们提出了相当多的求解方法,不仅有精确的启发式方法,还有元启发式方法。虽然使用精确的算法可以保证最优解,但当问题规模增加时,计算时间是最受关注的问题。启发式方法通常以非常快的速度提供解,但大多数是局部最优解。元启发式方法也是解决这个问题的另一种方法,它提供了更大的搜索空间。然而,它们中的大多数是基于需要大量参数设置的实验。本文提出了一种新的求解CVRPTW的有效方法,该方法在初始路由构建过程中采用了基于宽度优先搜索的图遍历和基于排序算法的几个概念,并在考虑容量约束和时间窗口的情况下,采用动态规划方法进行求解改进。与最先进的算法相比,所提出的方法的性能将在解决质量和计算时间方面非常胜任,而无需在参数设置上付出努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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