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3033224 
Journal Article 
Pheromone mark ant colony optimization with a hybrid node-based pheromone update strategy 
Deng, X; Zhang, L; Lin, H; Luo, Lan 
2015 
1 
Neurocomputing
ISSN: 0925-2312 
148 
46-53 
WOS:000343840000007 
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. 
Ant colony optimization; Pheromone mark; Node-based pheromone; k-nearest-neighbor nodes; PM-ACO; Shortest path problem