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Proceedings of the 12th annual conference companion on Genetic and evolutionary computation, 2010 This chapter mainly aims to introduce some widely used ACO algorithms and their origins, such as the AS, EAS, MMAS, and so on. It is found that all concerns are focused on the pheromone update strategy. Some uses the best-so-far-ant or the iteration-best ant independently/interactively to update the trail that ants travelled.
Xu, Benlian, Zhu, Jihong, Chen, Qinlan
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Scholarpedia, 2007 Article consultable à l'adresse suivante :http://www.scholarpedia.org/article/Ant_colony_optimization ; info:eu-repo/semantics ...
Marco Dorigo, Krzysztof Socha
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Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, 2009 ◮ Origins of ACO: Swarm intelligence ◮ How to transfer the biological inspiration into an algorithm ◮ Example applications of ACO: TSP and Assembly line balancing ◮ Hybridizations of ACO algorithms with more classical techniques Peer ...
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, 2012 NEGLI ULTIMI ANNI SONO STATE INTRODOTTE NUOVE METODOLOGIE PER L’OTTIMIZZAZIONE DI DETERMINATI TIPI DI PROBLEMI: OSSERVANDO E STUDIANDO MECCANISMI NATURALI È STATO POSSIBILE SVILUPPARE NUOVI ALGORITMI ADATTANDOLI POI A SITUAZIONI COMPLETAMENTE DIVERSE RISPETTO A QUELLE OSSERVATE IN NATURA.
Santino Madia +4 more
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Ant colony optimization theory: A survey
Theoretical Computer Science, 2005 Research on a new metaheuristic for optimization is often initially focused on proof-of-concept applications. It is only after experimental work has shown the practical interest of the method that researchers try to deepen their understanding of the method's functioning not only through more and more sophisticated experiments but also by means of an ...
Dorigo, Marco, Blum, Christian
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Ant Colony System Optimization. [PDF]
The Journal of Object Technology, 2009 Successful heuristic algorithms for solving combinatorial optimization problems have mimicked processes observed in nature. Two highly successful families of algorithms that do this are simulated annealing and genetic algorithms. Here, a third family of algorithms, ant colony optimization is explored and implemented in C#.
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Ant Colony Optimization with Cunning Ants
Transactions of the Japanese Society for Artificial Intelligence, 2007 In this paper, we propose the cAS, a new ACO algorithm, and evaluate the performance using TSP instances available at TSPLIB. The results show that cAS works well on the test instances and has performance that may be one of the most promising ACO algorithms.
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Ant colony optimization: A bibliometric review
Physics of Life ReviewsThis paper is a follow-up of one of the most-cited articles published in the first 20 years of the existence of Physics of Life Reviews. The specific topic is "ant colony optimization", which is a metaheuristic for solving challenging optimization problems.
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Distributed Optimization by Ant Colonies
, 1992 info:eu-repo/semantics ...
COLORNI VITALE, ALBERTO +2 more
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Ant Colony Optimization - Optimal Number of Ants
, 2018 The focus of this thesis paper is to study the impact the number of ants has on the found solution of the Ant Colony Optimization (ACO) metaheuristic when solving the Traveling Salesman Problem. The goal was to find out how the length of the computed tours change for different amounts of ants within a limited number of iterations.
Pettersson, Lars +1 more
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