Geodesic
Ant Colony Optimization Algorithm with Pheromone Correction Strategy for the Minimum Connected Dominating Set Problem
Computer Science and Information Systems, Tome 10 (2013) no. 1.

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In this paper an ant colony optimization (ACO) algorithm for the minimum connected dominating set problem (MCDSP) is presented. The MCDSP become increasingly important in recent years due to its applicability to the mobile ad hoc networks (MANETs) and sensor grids. We have implemented a one-step ACO algorithm based on a known simple greedy algorithm that has a significant drawback of being easily trapped in local optima. We have shown that by adding a pheromone correction strategy and dedicating special attention to the initial condition of the ACO algorithm this negative effect can be avoided. Using this approach it is possible to achieve good results without using the complex two-step ACO algorithm previously developed. We have tested our method on standard benchmark data and shown that it is competitive to the existing algorithms.
Keywords: Ant colony optimization (ACO), Minimum connected dominating set problem, Swarm intelligence, Optimization metaheuristics 
@article{CSIS_2013_10_1_a8,
     author = {Raka Jovanovic and Milan Tuba},
     title = {Ant {Colony} {Optimization} {Algorithm} with {Pheromone} {Correction} {Strategy} for the {Minimum} {Connected} {Dominating} {Set} {Problem}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {10},
     number = {1},
     year = {2013},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2013_10_1_a8/}
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Raka Jovanovic; Milan Tuba. Ant Colony Optimization Algorithm with Pheromone Correction Strategy for the Minimum Connected Dominating Set Problem. Computer Science and Information Systems, Tome 10 (2013) no. 1. http://geodesic.mathdoc.fr/item/CSIS_2013_10_1_a8/