A study of parallel approaches in MOACOs for solving the bicriteria TSP

Authors:
A. M. Mora;J. J. Merelo;P. A. Castillo;M. G. Arenas;P. García-Sánchez;J. L. J.;G. Romero
Affiliations:
Dpto. de Arquitectura y Tecnología de Computadores, Universidad de Granada, Spain;Dpto. de Arquitectura y Tecnología de Computadores, Universidad de Granada, Spain;Dpto. de Arquitectura y Tecnología de Computadores, Universidad de Granada, Spain;Dpto. de Arquitectura y Tecnología de Computadores, Universidad de Granada, Spain;Dpto. de Arquitectura y Tecnología de Computadores, Universidad de Granada, Spain;Dpto. de Arquitectura y Tecnología de Computadores, Universidad de Granada, Spain;Dpto. de Arquitectura y Tecnología de Computadores, Universidad de Granada, Spain
Venue:
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Year:
2011

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Abstract

In this work, the parallelization of some Multi-Objective Ant Colony Optimization (MOACO) algorithms has been performed. The aim is to get a better performance, not only in running time (usually the main objective when a distributed approach is implemented), but also improving the spread of solutions over the Pareto front (the ideal set of solutions). In order to do this, colony-level (coarse- grained) implementations have been tested for solving the Bicriteria TSP problem, yielding better sets of solutions, in the sense explained above, than a sequential approach.