Pheromone mark ant colony optimization with a hybrid node-based pheromone update strategy

被引:11
|
作者
Deng, Xiangyang [1 ]
Zhang, Limin [2 ]
Lin, Hongwen [1 ]
Luo, Lan [3 ]
机构
[1] Naval Aeronaut & Astronaut Univ, Dept Elect & Informat Engn, Yantai 264001, Peoples R China
[2] Naval Aeronaut & Astronaut Univ, Dept Sci Res, Yantai 264001, Peoples R China
[3] Yantai Vocat Coll, Basic Teaching Dept, Yantai 264001, Peoples R China
关键词
Ant colony optimization; Pheromone mark; Node-based pheromone; k-nearest-neighbor nodes; PM-ACO; Shortest path problem; ALGORITHM;
D O I
10.1016/j.neucom.2012.12.084
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An improved ant colony optimization (ACO) algorithm called pheromone mark ACO abbreviated PM-ACO is proposed for the non-ergodic optimal problems. PM-ACO associates the pheromone to nodes, and has a pheromone trace of scatter points which are referred to as pheromone marks. PM-ACO has a node-based pheromone update strategy, which includes two other rules except a best-so-far tour rule. One is called r-best-node update rule which updates the pheromones of the best-ranked nodes, which are selected by counting the nodes' passed ants in each iteration. The other one is called relevant-node depositing rule which updates the pheromones of the k-nearest-neighbor (KNN) nodes of a best-ranked node. Experimental results show that PM-ACO has a pheromone integration effect of some neighbor arcs on their central node, and it can result in instability. The improved PM-ACO has a good performance when applied in the shortest path problem. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:46 / 53
页数:8
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