A Compact Arc-Based ILP Formulation for the Pickup and Delivery Problem with Divisible Pickups and Deliveries

Author:

Jargalsaikhan Bolor1,Romeijnders Ward1ORCID,Roodbergen Kees Jan1ORCID

Affiliation:

1. Department of Operations, Faculty of Economics and Business, University of Groningen, 9747 AE Groningen, Netherlands

Abstract

We consider the capacitated single vehicle one-to-one pickup and delivery problem with divisible pickups and deliveries (PDPDPD). In this problem, we do not make the standard assumption of one-to-one pickup and delivery problems (PDPs) that each location has only one transportation request. Instead we assume there are multiple requests per location that may be performed individually. This may result in multiple visits to a location. We provide a new compact arc-based integer linear programming (ILP) formulation for the PDPDPD by deriving time-consistency constraints that identify the order in which selected outgoing arcs from a node are actually traversed. The formulation can also easily be applied to the one-to-one PDP by restricting the number of times that a node can be visited. Numerical results on standard one-to-one PDP test instances from the literature show that our compact formulation is almost competitive with tailor-made solution methods for the one-to-one PDP. Moreover, we observe that significant cost savings of up to 15% on average may be obtained by allowing divisible pickups and deliveries in one-to-one PDPs. It turns out that divisible pickups and deliveries are not only beneficial when the vehicle capacity is small, but also when this capacity is unrestrictive.

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

Subject

Transportation,Civil and Structural Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Mathematical modelling of the the one-to-one Pickup and Delivery Problem with time Windows with a single vehicle;2024 IEEE 15th International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA);2024-05-02

2. A Machine Learning-Based Algorithm for a Hybrid Two-Echelon Pickup and Delivery Problem;SSRN Electronic Journal;2022

3. Operational strategies for on-demand personal shopper services;Transportation Research Part C: Emerging Technologies;2021-09

4. Evaluating the Deployment of Collaborative Logistics Models for Local Delivery Services;Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems;2021

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3