Unmanned Aerial Vehicle hub-location and routing for monitoring geographic borders


APPLIED MATHEMATICAL MODELLING, vol.39, no.14, pp.3939-3953, 2015 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 39 Issue: 14
  • Publication Date: 2015
  • Doi Number: 10.1016/j.apm.2014.12.010
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.3939-3953
  • Keywords: p-Hub median, p-Hub location, Unmanned Aerial Vehicle, Border security, TRANSPORTATION, PROGRAM
  • Eskisehir Osmangazi University Affiliated: Yes


Recently, hub location problems have become more common with successful applications in air transportation. In this paper, we consider a hub-location and routing problem for border (Borders in this work refer to land borders, unless otherwise stated.) security in Turkey. Security is currently one of the most important issues. Countries are spending large amounts to prevent threats that may come from neighboring countries. Land borders are required to be monitored because of illegal border crossing activities and terrorist attacks. Various geographical restrictions at the borders can cause difficulties in monitoring and gathering the required data. We focus on selecting hubs among the airports run by the General Directorate of State Airports Authority of Turkey, the assignment of demand points to hubs and determining optimal routes for each hub. The study consists of two stages. First, the single allocation p-hub median problem is solved to determine the locations of the hubs for unmanned aircraft. To select hubs, the decision model uses an appropriateness parameter that is obtained by using ELECTRE, a multi-criteria decision-making tool. Five criteria are considered: The type of airport, the remoteness from threats, the proximity to a land border, the aerodrome traffic density and the time that the possible hubs are open to the air traffic. In the second stage, optimal routes are determined for each hub by using two mathematical models. The first model is cost-oriented and there is one vehicle per hub. In the second mathematical model for routing, the monitoring frequency parameters which means the priority of monitoring of the demand nodes obtained by using ELECTRE are used to maximize the monitoring frequency of the demand nodes. The criteria for demand nodes are (1) the need for UAVs, (2) illegal border crossing, and (3) the number of the illegal border activities and attacks. There are three vehicles per hub in the second model. The results of two mathematical models for routing problem are evaluated. (C) 2014 Elsevier Inc. All rights reserved.