Ángel Martín Ramírez Rabelo
Collective intelligence is an emergent property in multi-agent systems that achieve synchronization to optimize processes and tasks that, generally, a single agent could not carry out per se. There are systems where central coordination or direct communication between agents is not necessary for intelligent behavior to emerge collectively. For instance, in stigmergic systems, agents react to environmental modifications made by other agents without the need for direct interaction; such is the case of ant colonies. This behavior in ants inspired the development of algorithms based on these principles to solve hard problems in an approximate manner. In this work, we briefly review the application of this metaheuristic to the TSP and, in more detail, to the Bin Packing Problem (BPP). A Python implementation of ACO to solve the BPP is also proposed, and the adjustment of certain parameters—such as the number of ants, the number of generations, the relevance of the heuristic, and the pheromone evaporation factor—is studied.
@article{88e36f62-c99e-410f-9a80-61697dcb4ff2,
title={Implementation of an Ant Colony Algorith},
author={Ángel Martín Ramírez Rabelo},
year={2026},
language={en}
}TY - JOUR TI - Implementation of an Ant Colony Algorith AU - Ángel Martín Ramírez Rabelo PY - 2026 LA - en ER -
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