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9 results on '"Litovski, Ivan"'

1. Dynamics in Proportionate Selection.

Author

Agrawal, Abhishek, Mitchell, Ian, Passmore, Peter, Litovski, Ivan, Ribeiro, Bernardete, editor, Albrecht, Rudolf F., editor, Dobnikar, Andrej, editor, Pearson, David W., editor, and Steele, Nigel C., editor

Published
2005
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5. Dynamics in proportionate selection.

Author

Mitchell, Ian, Agrawal, Abhishek, Litovski, Ivan, Passmore, Peter J., Mitchell, Ian, Agrawal, Abhishek, Litovski, Ivan, and Passmore, Peter J.

Abstract

This paper reports experimental results of a test to investigate if an adaptive proportionate selection criteria for selecting individuals in a population can lead to improved results for Genetic Algorithms. The results were benchmarked against a symmetric TSP, which was chosen due to its NP-completeness, and it was shown that using such a technique did improve the results. The work forms the basis of a current PhD project at Middlesex University.

Published
2005

9. Dynamics in Proportionate Selection.

Author

Ribeiro, Bernardete, Albrecht, Rudolf F., Dobnikar, Andrej, Pearson, David W., Steele, Nigel C., Agrawal, Abhishek, Mitchell, Ian, Passmore, Peter, and Litovski, Ivan

Subjects
GENETIC algorithms, STOCHASTIC convergence, COMBINATORIAL optimization, ALGORITHMS, MATHEMATICAL functions
Abstract

This paper proposes a new selection method for Genetic Algorithms. The motivation behind the proposed method is to investigate the effect of different selection methods on the rate of convergence. The new method Dynamic Selection Method (DSM) is based on proportionate selection. DSM functions by continuously changing the criteria for parent selection (dynamic) based on the number of generations in a run and the current generation. Results show that by using DSM to maintain diversity in a population gives slower convergence, but, their overall performance was an improvement. Relationship between slower convergences, in GA runs, leading to better solutions, has been identified. [ABSTRACT FROM AUTHOR]

Published
2005
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