Randomized algorithms
Some Guidelines for Genetic Algorithms with Penalty Functions
Proceedings of the 3rd International Conference on Genetic Algorithms
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
A Probabilistic Algorithm for k-SAT and Constraint Satisfaction Problems
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
An overview of evolutionary algorithms for parameter optimization
Evolutionary Computation
Comparison of Certain Evolutionary Algorithms
Automation and Remote Control
Comparing evolutionary algorithms to the (1+1) -EA
Theoretical Computer Science
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This work presents an experimental comparison of the steady-state genetic algorithm to the (1+1)-evolutionary algorithm applied to the maximum vertex independent set problem. The penalty approach is used for both algorithms and tuning of the penalty function is considered in the first part of the paper. In the second part we give some reasons why one could expect the competitive performance of the (1+1)-EA. The results of computational experiment are presented.