Fixed-parameter tractability and completeness II: on completeness for W[1]
Theoretical Computer Science
Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Neural Networks for Combinatorial Optimization: a Review of More Than a Decade of Research
INFORMS Journal on Computing
Upper bounds for vertex cover further improved
STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
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The minimum vertex cover problem is a classic graph optimization problem. It is well known that it is an NP-complete problem. In this paper, an efficient simulated annealing algorithm is presented for the minimum vertex cover problem. In this algorithm, an acceptance function is defined for every vertex. This can help the algorithm in finding a near-optimal solution to a problem. Simulations are performed on several benchmark graphs, and the simulation results show that the proposed algorithm provides a high probability of finding optimal solutions.