Issue |
RAIRO-Oper. Res.
Volume 56, Number 5, September-October 2022
|
|
---|---|---|
Page(s) | 3733 - 3763 | |
DOI | https://doi.org/10.1051/ro/2022170 | |
Published online | 01 November 2022 |
Mathematical modeling of a bi-objective hub location-routing problem for rapid transit networks
1
Department of Industrial Engineering, Yazd University, Yazd, Iran
2
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
* Corresponding author: mhonarvar@yazd.ac.ir
Received:
26
July
2022
Accepted:
28
September
2022
This paper aims to develop a mathematical model for rapid transit networks based on a hub and spoke model, comprising stopovers (stations) in the hub and non-hub (spoke) alignments. Due to the use of rapid transit systems in both the hub-level sub-network (i.e., the network among the hub nodes) and the spoke-level sub-network (i.e., the network which connect the spoke nodes to each other and to the hub nodes), the proposed model relaxes some of the usual assumptions in classical hub location models. In the proposed model, the transshipment of flows among the spoke nodes is possible, the setup costs of all the hub and spoke nodes and edges are considerable, and both hub and spoke edges have capacity constraints. In addition to the network infrastructure designed through decisions about the locations of the hub and spoke nodes and edges, the hub and spoke rapid transit lines are determined along with the routes of demands in those lines. The model incorporates profit and service time criteria. An adaptive large neighborhood search solution algorithm is developed whose efficiency is proved by the computational results. Some managerial insight is also provided through the analysis of the resulting networks under various parameter settings.
Mathematics Subject Classification: 90B06
Key words: Hub location / hub and spoke network / rapid transit network / line planning / adaptive large neighborhood search / bi-objective optimization
© The authors. Published by EDP Sciences, ROADEF, SMAI 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.