Solving Heterogeneous Fleet Multiple Depot Vehicle Scheduling Problem as an Asymmetric Traveling Salesman Problem

  • Jorge Alpedrinha Ramos
  • Luís Paulo Reis
  • Dulce Pedrosa
Conference paper

DOI: 10.1007/978-3-642-24769-9_8

Part of the Lecture Notes in Computer Science book series (LNCS, volume 7026)
Cite this paper as:
Ramos J.A., Reis L.P., Pedrosa D. (2011) Solving Heterogeneous Fleet Multiple Depot Vehicle Scheduling Problem as an Asymmetric Traveling Salesman Problem. In: Antunes L., Pinto H.S. (eds) Progress in Artificial Intelligence. EPIA 2011. Lecture Notes in Computer Science, vol 7026. Springer, Berlin, Heidelberg

Abstract

The Vehicle Scheduling Problem is a well-known combinatorial optimization problem that emerges in mobility and transportation sectors. The heterogeneous fleet with multiple depots extension arises in major urban public transportation companies due to different demands throughout the day and some restrictions in the use of different vehicle types. This extension introduces complexity to the problem and makes the known deterministic methods unable to solve it efficiently. This paper describes an approach to create a comprehensive model to represent the Multiple Depot Vehicle Scheduling Problem as an Asymmetric Traveling Salesman Problem. To solve the A-TSP problem an Ant Colony based meta-heuristic was developed. The results achieved on solving problems from a Portuguese major public transportation planning database show the usefulness of the proposed approach.

Keywords

HFMDVSP Multiple Depot Vehicle Scheduling Problem Traveling Salesman Problem A-TSP Ant Colony System 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jorge Alpedrinha Ramos
    • 1
  • Luís Paulo Reis
    • 2
  • Dulce Pedrosa
    • 3
  1. 1.DEI - Departamento de Engenharia InformáticaFaculdade de Engenharia da Universidade do PortoPortugal
  2. 2.LIACC - Laboratório de Inteligência Artificial e Ciência de Computadores da Universidade do PortoFaculdade de Engenharia da Universidade do PortoPortugal
  3. 3.OPT - Optimização e Planeamento de TransportesPortugal

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