A survey: Ant Colony Optimization based recent research and implementation on several engineering domain

被引:230
作者
Mohan, B. Chandra [1 ]
Baskaran, R. [1 ]
机构
[1] Anna Univ, Dept Comp Sci & Engn, Madras 600025, Tamil Nadu, India
关键词
Swarm Intelligence; Ant Colony Optimization; Soft-computing; Engineering applications; ALGORITHM; MANAGEMENT; MODELS;
D O I
10.1016/j.eswa.2011.09.076
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
Ant Colony Optimization (ACO) is a Swarm Intelligence technique which inspired from the foraging behaviour of real ant colonies. The ants deposit pheromone on the ground in order to mark the route for identification of their routes from the nest to food that should be followed by other members of the colony. This ACO exploits an optimization mechanism for solving discrete optimization problems in various engineering domain. From the early nineties, when the first Ant Colony Optimization algorithm was proposed. ACO attracted the attention of increasing numbers of researchers and many successful applications are now available. Moreover, a substantial corpus of theoretical results is becoming available that provides useful guidelines to researchers and practitioners in further applications of ACO. This paper review varies recent research and implementation of ACO, and proposed a modified ACO model which is applied for network routing problem and compared with existing traditional routing algorithms. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:4618 / 4627
页数:10
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