CHAC. A MOACO Algorithm for Computation of Bi-Criteria Military Unit Path in the Battlefield

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dc.creatorMora, A. M.
dc.creatorMerelo, J. J.
dc.creatorMillan, C.
dc.creatorTorrecillas, J.
dc.creatorLaredo, J. L. J.
dc.date2006-10-19
dc.date.accessioned2026-07-07T07:27:53Z
dc.date.available2026-07-07T07:27:53Z
dc.descriptionIn this paper we propose a Multi-Objective Ant Colony Optimization (MOACO) algorithm called CHAC, which has been designed to solve the problem of finding the path on a map (corresponding to a simulated battlefield) that minimizes resources while maximizing safety. CHAC has been tested with two different state transition rules: an aggregative function that combines the heuristic and pheromone information of both objectives and a second one that is based on the dominance concept of multiobjective optimization problems. These rules have been evaluated in several different situations (maps with different degree of difficulty), and we have found that they yield better results than a greedy algorithm (taken as baseline) in addition to a military behaviour that is also better in the tactical sense. The aggregative function, in general, yields better results than the one based on dominance.
dc.identifierhttps://arxiv.org/abs/cs/0610113
dc.identifierhttp://arxiv.org/abs/cs/0610113
dc.identifierPublished in Proceedings of the Workshop on Nature Inspired Cooperative Strategies for Optimization. NICSO'2006, Pelta & Krasnogor, (eds) pp 85-98, Jun. 2006
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/117535
dc.subjectMultiagent Systems
dc.subjectComputational Complexity
dc.titleCHAC. A MOACO Algorithm for Computation of Bi-Criteria Military Unit Path in the Battlefield
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