On the capacity inequalities for the heterogeneous vehicle routing problem

IF 0.9 4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Konstantin Pavlikov
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引用次数: 0

Abstract

Fractional and Rounded capacity inequalities are two important families of valid inequalities known for the homogeneous Capacitated Vehicle Routing Problem (CVRP). Such inequalities impose the minimum number of vehicles required to service each and every subset of customers, be it a fractional or an integer value. In case of the Heterogeneous version of the routing problem (HCVRP), the minimum number of vehicles required for a subset of customers is not defined uniquely: it depends on the vehicle types and fleet composition that was engaged in serving the customers. This paper revises existing literature on the capacity-based valid inequalities for the HCVRP and presents new routines to separate them exactly using mixed integer linear programming (MILP). In addition, this paper proposes a new family of capacity-based valid inequalities for the HCVRP together with an exact routine to separate them. A computational study demonstrates applicability of considered inequalities in solving HCVRP instances using a standard MILP solver.
异构车辆路径问题的容量不等式
分数容量不等式和舍入容量不等式是齐次有容车辆路径问题的两类重要有效不等式。这样的不平等规定了为每个客户子集提供服务所需的最小车辆数量,无论是小数还是整数值。在路由问题的异构版本(HCVRP)的情况下,客户子集所需的最小车辆数量不是唯一定义的:它取决于为客户服务的车辆类型和车队组成。本文对现有文献中基于容量的HCVRP有效不等式进行了修正,提出了利用混合整数线性规划(MILP)精确分离它们的新方法。此外,本文还提出了一种新的基于能力的有效不等式族,并给出了分离它们的精确例程。一项计算研究证明了使用标准MILP求解器求解HCVRP实例时考虑的不等式的适用性。
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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来源期刊
Operations Research Letters
Operations Research Letters 管理科学-运筹学与管理科学
CiteScore
2.10
自引率
9.10%
发文量
111
审稿时长
83 days
期刊介绍: Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.
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