Ant colony optimization algorithm based on pheromone diffusion

Guo Rui Huang; Xian Bin Cao; Xu Fa Wang

Ant colony optimization algorithm based on pheromone diffusion

Guo Rui Huang^*
, Xian Bin Cao
, Xu Fa Wang

^*Corresponding author for this work

University of Science and Technology of China

Research output: Contribution to journal › Article › peer-review

43 Scopus citations

Abstract

Ant Colony Optimization (AGO) Algorithm is a novel search algorithm which simulates the social behavior of ant colony depending on pheromone's communication. Based on the analysis of shortcomings of basic AGO such as lack and lag of collaboration among ants, this paper proposes a new AGO which is more faithful to real ant colony system. By setting up the pheromone diffusion model, this algorithm improves the collaboration among ants which are nearby. The simulation results for TSP problem show the validity of it.

Original language	English
Pages (from-to)	865-868
Number of pages	4
Journal	Tien Tzu Hsueh Pao/Acta Electronica Sinica
Volume	32
Issue number	5
State	Published - May 2004
Externally published	Yes

Keywords

Ant colony optimization algorithm
Ant colony system
Diffusion mechanism
Pheromone

Cite this

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title = "Ant colony optimization algorithm based on pheromone diffusion",

abstract = "Ant Colony Optimization (AGO) Algorithm is a novel search algorithm which simulates the social behavior of ant colony depending on pheromone's communication. Based on the analysis of shortcomings of basic AGO such as lack and lag of collaboration among ants, this paper proposes a new AGO which is more faithful to real ant colony system. By setting up the pheromone diffusion model, this algorithm improves the collaboration among ants which are nearby. The simulation results for TSP problem show the validity of it.",

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AU - Cao, Xian Bin

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AB - Ant Colony Optimization (AGO) Algorithm is a novel search algorithm which simulates the social behavior of ant colony depending on pheromone's communication. Based on the analysis of shortcomings of basic AGO such as lack and lag of collaboration among ants, this paper proposes a new AGO which is more faithful to real ant colony system. By setting up the pheromone diffusion model, this algorithm improves the collaboration among ants which are nearby. The simulation results for TSP problem show the validity of it.

KW - Ant colony optimization algorithm

KW - Ant colony system

KW - Diffusion mechanism

KW - Pheromone

UR - https://www.scopus.com/pages/publications/3442890365

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SN - 0372-2112

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JF - Tien Tzu Hsueh Pao/Acta Electronica Sinica

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Ant colony optimization algorithm based on pheromone diffusion

Abstract

Keywords

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