Displaying similar documents to “A review on the ant colony optimization metaheuristic: basis, models and new trends.”

Experiments with variants of ant algorithms.

Thomas Stützle, Sebastian Linke (2002)

Mathware and Soft Computing

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A number of extensions of Ant System, the first ant colony optimization (ACO) algorithm, were proposed in the literature. These extensions typically achieve much improved computational results when compared to the original Ant System. However, many design choices of Ant System are left untouched including the fact that solutions are constructed, that real-numbers are used to simulate pheromone trails, and that explicit pheromone evaporation is used. In this article we experimentally...

Adaptive search heuristics for the generalized assignment problem.

Helena Ramalhinho Lourenço, Daniel Serra (2002)

Mathware and Soft Computing

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The Generalized Assignment Problem consists of assigning a set of tasks to a set of agents at minimum cost. Each agent has a limited amount of a single resource and each task must be assigned to one and only one agent, requiring a certain amount of the agent's resource. We present the application of a MAX-MIN Ant System (MMAS) and a greedy randomized adaptive search procedure (GRASP) to the generalized assignment problem based on hybrid approaches. The MMAS heuristic can be seen as an...

Editorial

Clarisse Dhaenens, Patrick Siarry, El-Ghazali Talbi (2008)

RAIRO - Operations Research

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Ant Colony Optimisation: models and applications.

Oscar Cordón, Francisco Herrera, Thomas Stützle (2002)

Mathware and Soft Computing

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Ant Colony Optimization (ACO) is a metaheuristic that is inspired by the shortest path searching behavior of various ant species [1,2]. The initial work of Dorigo, Maniezzo and Colorni [3,4] who proposed the first ACO algorithm called Ant System, has stimulated a still strongly increasing number of researchers to develop more sophisticated and better performing ACO algorithms that are used to successfully solve a large number of hard combinatorial optimization problems such as the traveling...

Towards a theory of practice in metaheuristics design: A machine learning perspective

Mauro Birattari, Mark Zlochin, Marco Dorigo (2006)

RAIRO - Theoretical Informatics and Applications

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A number of methodological papers published during the last years testify that a need for a thorough revision of the research methodology is felt by the operations research community – see, for example, [Barr (1995) 9–32; Eiben and Jelasity, 582–587; Hooker, (1995) 33–42; Rardin and Uzsoy, (2001) 261–304]. In particular, the performance evaluation of nondeterministic methods, including widely studied metaheuristics such as evolutionary...