The profit-oriented hub line location problem with elastic demand

  1. Brenda Cobeña 2
  2. Iván Contreras 2
  3. Luisa I. Martínez-Merino 1
  4. Antonio M. Rodríguez-Chía 1
  1. 1 Universidad de Cádiz, Spain.
  2. 2 Concordia University and Interuniversity Research Centre on Enterprise Networks, Logistics, and Transportation, Canada.
Actas:
XII International Workshop on Locational Analysis and Related Problems 2023, Edinburgh

Editorial: https://redloca.ulpgc.es/en/redloca23.html

ISBN: 978-84-09-53463-0

Año de publicación: 2023

Páginas: 35-36

Tipo: Aportación congreso

Resumen

The hub line location problem (HLLP) was introduced in [1] and it has relevant applications in public transportation planning design (tram, subways, express bus lane, etc.) and road network design. The aim of the HLLP is to locate p hubs connected by a path that is composed by p-1hub arcs in such a way that the total travel time of the origin-destination pairs is minimized. If the direct travel time between an origin-destinationis smaller than any path using the line, the demand is routed without using the hub line. HLLP assumes that demand between each origin and destination can be a priori estimated and that the resulting constructed hub line network does not have any effect on the demand.In this work, we extend the HLLP. Particularly, we introduce the profitoriented hub line location problem with elastic demand (ED-HLLP). Thismodel uses a gravity model to include the elasticity of demand. Gravity models have been previously used to model elastic demand in networkdesign problems, see [2]. The main goal of ED-HLLP is to maximize the revenue of the total time reduction provided by the hub line consideringelastic demand. Thus, this new model takes into account the long-term impact on the demands that opening a hub line can have. We propose different non-linear formulations to address this problem. The main difference between these formulations is the way in which the line structure is modeled. Besides, we introduce three main linear formulations. These linear formulations use the possible paths using the hub line as variables. Consequently, it is necessary to use a preprocessing phase that calculates the candidate paths for each origin-destination. For this preprocessing phase, we provide efficient algorithms to create all possible candidate paths. Finally, we also present a computational experience that evaluates the strengths and limits of these formulations for ED-HLLP.