Journal ArticleDOI
An ant colony optimization algorithm for the minimum weight vertex cover problem
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TLDR
A meta-heuristic based upon the Ant Colony Optimization (ACO) approach, to find approximate solutions to the minimum weight vertex cover problem, which incorporates several new features so as to select vertices out of the vertex set whereas the total weight can be minimized as much as possible.Abstract:
Given an undirected graph and a weighting function defined on the vertex set, the minimum weight vertex cover problem is to find a vertex subset whose total weight is minimum subject to the premise that the selected vertices cover all edges in the graph. In this paper, we introduce a meta-heuristic based upon the Ant Colony Optimization (ACO) approach, to find approximate solutions to the minimum weight vertex cover problem. In the literature, the ACO approach has been successfully applied to several well-known combinatorial optimization problems whose solutions might be in the form of paths on the associated graphs. A solution to the minimum weight vertex cover problem however needs not to constitute a path. The ACO algorithm proposed in this paper incorporates several new features so as to select vertices out of the vertex set whereas the total weight can be minimized as much as possible. Computational experiments are designed and conducted to study the performance of our proposed approach. Numerical results evince that the ACO algorithm demonstrates significant effectiveness and robustness in solving the minimum weight vertex cover problem.read more
Citations
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Journal ArticleDOI
Local search with edge weighting and configuration checking heuristics for minimum vertex cover
TL;DR: The experimental results conclude that EWLS and EWCC are largely competitive on DIMACS benchmarks, where they outperform other current best heuristic algorithms on most hard instances, and dominate on the hard random BHOSLIB benchmarks.
Journal ArticleDOI
Application of ant colony optimization for no-wait flowshop scheduling problem to minimize the total completion time
TL;DR: An application of the ACO to a two-machine flowshop scheduling problem, where no intermediate storage is available between two machines and each operation demands a setup time on the machines, demonstrates the success of ACO's applications to the scheduling problem of interest.
Journal ArticleDOI
An effective ant colony optimization algorithm (ACO) for multi-objective resource allocation problem (MORAP)
TL;DR: A modified version of ant colony optimization (ACO) is proposed, in this algorithm the efficiency of algorithm is increased by increasing the learning of ants, to obtain a set of Pareto solution efficiently.
Journal ArticleDOI
NuMVC: an efficient local search algorithm for minimum vertex cover
TL;DR: A new MVC local search algorithm, referred to as NuMVC, which is at least competitive with the nearest competitor namely PLS on the DIMACS benchmark, and clearly dominates all competitors on the BHOSLIB benchmark.
Journal ArticleDOI
An ant colony optimization algorithm with improved pheromone correction strategy for the minimum weight vertex cover problem
Raka Jovanovic,Milan Tuba +1 more
TL;DR: This article proposes a pheromone correction heuristic strategy that uses information about the best-found solution to exclude suspicious elements from it and improves pure ant colony optimization algorithm by avoiding early trapping in local convergence.
References
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