Solving the Generalized Vertex Cover Problem by Genetic Algorithm
keywords: Vertex cover, genetic algorithms, evolutionary approach, combinatorial optimization, graph algorithms
In this paper an evolutionary approach to solving the generalized vertex cover problem (GVCP) is presented. Binary representation and standard genetic operators are used along with the appropriate objective function. The experiments were carried out on randomly generated instances with up to 500 vertices and 100 000 edges. Performance of the genetic algorithm (GA) is compared with CPLEX solver and 2-approximation algorithm based on LP relaxation. The genetic algorithm outperformed both CPLEX solver and 2-approximation heuristic.
reference: Vol. 29, 2010, No. 6+, pp. 1251–1265
