Swarm Intelligence

, Volume 1, Issue 2, pp 135–151

Ant colony optimization for real-world vehicle routing problems

From theory to applications
  • A. E. Rizzoli
  • R. Montemanni
  • E. Lucibello
  • L. M. Gambardella
Article

DOI: 10.1007/s11721-007-0005-x

Cite this article as:
Rizzoli, A.E., Montemanni, R., Lucibello, E. et al. Swarm Intell (2007) 1: 135. doi:10.1007/s11721-007-0005-x

Abstract

Ant colony optimization (ACO) is a metaheuristic for combinatorial optimization problems. In this paper we report on its successful application to the vehicle routing problem (VRP). First, we introduce the VRP and some of its variants, such as the VRP with time windows, the time dependent VRP, the VRP with pickup and delivery, and the dynamic VRP. These variants have been formulated in order to bring the VRP closer to the kind of situations encountered in the real-world.

Then, we introduce the basic principles of ant colony optimization, and we briefly present its application to the solution of the VRP and of its variants.

Last, we discuss the applications of ACO to a number of real-world problems: a VRP with time windows for a major supermarket chain in Switzerland; a VRP with pickup and delivery for a leading distribution company in Italy; a time dependent VRP for freight distribution in the city of Padua, Italy, where the travel times depend on the time of the day; and an on-line VRP in the city of Lugano, Switzerland, where customers’ orders arrive during the delivery process.

Keywords

Ant colony optimization Ant colony system Vehicle routing problem Dynamic VRP Rich VRP Real-world VRP 

Copyright information

© Springer Science + Business Media, LLC 2007

Authors and Affiliations

  • A. E. Rizzoli
    • 1
  • R. Montemanni
    • 1
  • E. Lucibello
    • 2
  • L. M. Gambardella
    • 1
  1. 1.Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA)MannoSwitzerland
  2. 2.AntOptimaLuganoSwitzerland

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