The Hub Line Location Problem

Abstract

T his paper presents the hub line location problem in which the location of a set of hub facilities connected by means of a path (or line) is considered. Potential applications arise in the design of public transportation and rapid transit systems, where network design costs greatly dominate routing costs and thus full interconnection of hub facilities is unrealistic. Given that service time is the predominant objective in these applications, the problem considers the minimization of the total weighted travel time between origin/destination nodes while taking into account the time spent to access and exit the hub line. An exact algorithm based on a Benders decomposition of a strong path-based formulation is proposed. The standard decomposition method is enhanced through the incorporation of several features such as a multicut strategy, an efficient algorithm to solve the subproblem and to obtain stronger optimality cuts, and a Benders branch-and-cut scheme that requires the solution of only one master problem. Computational results obtained on benchmark instances with up to 100 nodes confirm the efficiency of the proposed algorithm, which is considerably faster and able to solve larger instances than a general purpose solver.

A Benders decomposition approach for the charging station location problem with plug-in hybrid electric vehicles

“…Considering PHEVs beside EVs further compound the challenge in the charging station location problem. There are several successful implementations of Benders decomposition ( Benders, 1962 ) for location problems in the recent literature ( de Camargo et al, 20 08; 20 09; Contreras et al, 2011; Cordeau et al, 20 0 0; 20 01; Costa, 20 05; Fontaine and Minner, 2014;Froyland et al, 2013;Khatami et al, 2015;Martins de Sá et al, 2015;de Sá et al, 2013;Wheatley et al, 2015;Wu et al, 2005 ). In this section, we propose a BD algorithm as the solution technique and apply enhancements to improve the solution time of the algorithm by efficiently solving the subproblem and constructing Pareto-optimal cuts in closed form expressions.…”

A Multimodal Passenger-and-Package Sharing Network for Urban Logistics

“…Typically, the hubs are completely connected. However, in some special cases, incomplete interhub network structures, e.g., ring [39], star [40], tree [41,42], and line [43], are adopted. In terms of the design of spoke links for flow assignment, a demand node can be connected to one or multiple hubs, i.e., single or multiple assignment structures.…”

“…In terms of the design of spoke links for flow assignment, a demand node can be connected to one or multiple hubs, i.e., single or multiple assignment structures. Aykin [44] and Martins de Sá et al [43] extend the topology of spoke links by considering that the flows between some OD pairs can be shipped directly without being routed through hubs. Besides direct links, Lin and Chen [45] integrate stopovers and feeders to the network.…”

Evaluating the Market Share of China Railway Express Lines – A Data-driven Approach

“…Cullinane and Wilmsmeier [9] stress the significance of dry ports, claiming that dry ports will be applied more and more in the future. Martins de Sá et al [10] focus on the hub line location problem and put forward an exact algorithm based on a Benders decomposition of a strong path-based formulation. Ishfaq and Sox [11,12] address the strategic planning for an interregional, hub-based, intermodal logistics network operated by a logistics service provider and use taboo search meta-heuristic to solve this problem.…”