Parallel Approaches in MOACOs for Solving the Bi-criteria TSP: A Preliminary Study

  • A. M. Mora
  • P. A. Castillo
  • M. G. Arenas
  • P. García-Sánchez
  • J. L. J. Laredo
  • J. J. Merelo
Part of the Studies in Computational Intelligence book series (SCI, volume 422)

Abstract

This work presents two parallelization schemes applied to three different Multi-Objective Ant Colony Optimization (MOACO) algorithms. The aim is to get a better performance, improving the quality, quantity and the spread of solutions over the Pareto Front (the ideal set of solutions), rather than just reduce the running time. Colony-level (coarse-grained) implementations have been tested for solving two instances of the Bi-criteria TSP problem, yielding better sets of solutions, in the mentioned sense, than the correspondent sequential approach.

Keywords

Pareto Front Travelling Salesman Problem Vehicle Route Problem Heuristic Function Vehicle Route Problem With Time Window 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • A. M. Mora
    • 1
  • P. A. Castillo
    • 1
  • M. G. Arenas
    • 1
  • P. García-Sánchez
    • 1
  • J. L. J. Laredo
    • 1
  • J. J. Merelo
    • 1
  1. 1.Departamento de Arquitectura y Tecnología de ComputadoresUniversidad de GranadaGranadaSpain

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