Cristian Millán

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In 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(More)
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)
hCHAC, a MOACO implemented to solve the problem of finding the path that minimizes resources, while maximizing safety for a military unit in realistic battlefields, is compared with some other approaches: two extreme methods, which only considers one objective in the search, and a mono-objective algorithm, which combines the two objectives terms of the(More)
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