On the limited memory BFGS method for large scale optimization
Mathematical Programming: Series A and B
Future Generation Computer Systems
The Ant Colony Metaphor for Searching Continuous Design Spaces
Selected Papers from AISB Workshop on Evolutionary Computing
Ant Colony Optimization
A Population-based Approach for Hard Global Optimization Problems based on Dissimilarity Measures
Mathematical Programming: Series A and B
Global Optimization of Morse Clusters by Potential Energy Transformations
INFORMS Journal on Computing
An incremental ant colony algorithm with local search for continuous optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
An enhanced aggregation pheromone system for real-parameter optimization in the ACO metaphor
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
The hyper-cube framework for ant colony optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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We present a discrete ant colony algorithm to cluster geometry optimization. To deal with this continuous problem, the optimization framework includes functions to map solutions across the discrete and continuous spaces. Results obtained with short-ranged Morse clusters show that the proposed approach is effective, scalable and is competitive with state-of the-art optimization methods specifically designed to tackle continuous domains. A detailed analysis is presented to help to gain insight into the role played by several components of the ant colony algorithm.