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Book Sections Year : 2016

Introducing the Environment in Ant Colony Optimization

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Abstract

Meta-heuristics are general-purpose methods for global optimization, which take generally inspiration from natural behaviors and phenomena. Among the others, Ant Colony Optimization (ACO) received particular interest in the last years. In this work, we introduce the environment in ACO, for the meta-heuristic to perform amore realistic simulation of the ants' behavior. Computational experiments on instances of the GPS Surveying Problem (GSP) show that the introduction of the environment in ACO allows us to improve the quality of obtained solutions.
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Dates and versions

hal-01402423 , version 1 (24-11-2016)

Identifiers

  • HAL Id : hal-01402423 , version 1

Cite

Antonio Mucherino, Stefka Fidanova, Maria Ganzha. Introducing the Environment in Ant Colony Optimization. Studies in Computational Intelligence, 655, Springer, pp.147-158, 2016, Recent Advances in Computational Optimization. ⟨hal-01402423⟩
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