Ant Colony Optimization Algorithm Model Based on the Continuous Space

Authors

  • Xuepeng Huang Hubei University of Police, Wuhan, China

DOI:

https://doi.org/10.3991/ijoe.v12i12.6451

Keywords:

ant colony algorithm, pheromone, continuous space optimization

Abstract


Ant colony algorithm is a heuristic algorithm which is　fit for solving complicated combination optimization.It showed great advantage on solving combinatorial optimization problem since it was proposed. The algorithm uses distributed parallel computing and positive feedback mechanism, and is easy to combine with other algorithms.This ant colony algorithm has already been widespread used in the field of discrete space optimization, however, is has been rarely used for continuous space optimization question.On the basis of basic ant colony algorithm principles and mathematical model, this paper proposes an ant colony algorithm for solving continuous space optimization question.Comparing with the ant colony algorithm, the new algorithm improves the algorithm in aspects of ant colony initialization, information density function, distribution algorithms, direction of ant colonymotion, and so on. The new algorithm uses multiple optimization strategy, such as polynomial time reduction and branching factor, and improves the ant colony algorithm effectively.

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Published

2016-12-25

How to Cite

Huang, X. (2016). Ant Colony Optimization Algorithm Model Based on the Continuous Space. International Journal of Online and Biomedical Engineering (iJOE), 12(12), pp. 27–31. https://doi.org/10.3991/ijoe.v12i12.6451

Issue

Vol. 12 No. 12 (2016)

Section

Papers

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