An ACO algorithm for the shortest common supersequence problem
New ideas in optimization
Ant Colony Optimization
A new hybrid heuristic approach for solving large traveling salesman problem
Information Sciences—Informatics and Computer Science: An International Journal
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
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In this paper we propose a multi-colony ant colony optimization architecture. In this approach several colonies try to simultaneously solve a problem. Each colony has its own trail and set of control parameters, ensuring that different search strategies are used throughout the optimization. Moreover, the most successful colonies contribute with information that help others with poor behavior to enhance their performance. A first version of the multi-colony approach was applied to the optimal node placement, an important optimization problem from the network communication field. We report some preliminary results obtained with several benchmark instances. They show that the proposed algorithm is promising, as it was able to outperform a single-colony approach. We conclude this paper with a discussion about research directions for the near future, which are related to a more detailed analysis of the existing architecture and to a number of extensions we are planning to implement and analyze.