A PRUNING BASED ANT COLONY ALGORITHM FOR MINIMUM VERTEX COVER PROBLEM

Given an undirected, unweighted graph G = (V, E) the minimum vertex cover (MVC) problem is a subset of V whose cardinality is minimum subject to the premise that the selected vertices cover all edges in the graph. In this paper, we propose a meta-heuristic based on Ant Colony Optimization (ACO) approach to find approximate solutions to the minimum vertex cover problem. By introducing a visible set based on pruning paradigm for ants, in each step of their traversal, they are not forced to consider all of the remaining vertices to select the next one for continuing the traversal, resulting very high improvement in both time and convergence rate of the algorithm. We compare our algorithm with two existing algorithms which are based on Genetic Algorithms (GAs) as well as its testing on a variety of benchmarks. Computational experiments evince that the ACO algorithm demonstrates much effectiveness and consistency for solving the minimum vertex cover problem.