Enhancing a MOACO for Solving the Bi-criteria Pathfinding Problem for a Military Unit in a Realistic Battlefield

Authors:
Antonio Miguel Mora;Juan Julian Merelo;Cristian Millan;Juan Torrecillas;Juan Luís Laredo;Pedro A. Castillo
Affiliations:
Departamento de Arquitectura y Tecnología de Computadores. University of Granada, Spain);Departamento de Arquitectura y Tecnología de Computadores. University of Granada, Spain);Mando de Adiestramiento y Doctrina. Spanish Army,;Mando de Adiestramiento y Doctrina. Spanish Army,;Departamento de Arquitectura y Tecnología de Computadores. University of Granada, Spain);Departamento de Arquitectura y Tecnología de Computadores. University of Granada, Spain)
Venue:
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Year:
2009

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Abstract

CHAC, a Multi-Objective Ant Colony Optimization (MOACO), has been designed to solve the problem of finding the path that minimizes resources while maximizing safety for a military unit. The new version presented in this paper takes into acount new, more realistic, conditions and constraints. CHAC's previously proposed transition rules have been tested in more realistic maps. In addition some improvements in the implementation have been made, so better solutions are yielded. These solutions are better than a baseline greedy algorithm, and still good from a military point of view.