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This work evaluates an enhanced ACO pheromone structure that improves performance in multi-objective optimization, suggesting its effectiveness in complex problem-solving.
In this work, we investigate an approach that enriches the information encoded within the ACO pheromone structure in order to enhance the performance of swarm optimization. While this concept has been extensively studied in the context of single-objective optimization, this paper provides a comprehensive evaluation of its extension to multi-objective optimization problems. The results demonstrate that this enhanced pheromone representation remains effective in multi-objective settings.
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Starzec et al. (2026) studied this question.
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