In this paper we study cellular evolutionary algorithms, a kind of decentralized heuristics, and the importance of their induced exploration/exploitation balance on different problems. It is shown that, by choosing synchronous or asynchronous update policies, the selection pressure, and thus the exploration/exploitation tradeoff, can be influenced directly, without using additional ad hoc parameters. Synchronous algorithms of different neighborhood-to-topology ratio, and asynchronous update policies are applied to a set of benchmark problems. Our conclusions show that the update methods of the asynchronous versions, as well as the ratio of the decentralized algorithm, have a marked influence on its convergence and on its accuracy.

The Influence of Grid Shape and Asynchronocity on Cellular Evolutionary Algorithms

GIACOBINI, Mario Dante Lucio;
2004-01-01

Abstract

In this paper we study cellular evolutionary algorithms, a kind of decentralized heuristics, and the importance of their induced exploration/exploitation balance on different problems. It is shown that, by choosing synchronous or asynchronous update policies, the selection pressure, and thus the exploration/exploitation tradeoff, can be influenced directly, without using additional ad hoc parameters. Synchronous algorithms of different neighborhood-to-topology ratio, and asynchronous update policies are applied to a set of benchmark problems. Our conclusions show that the update methods of the asynchronous versions, as well as the ratio of the decentralized algorithm, have a marked influence on its convergence and on its accuracy.
2004
Congress on Evolutionary Computation, CEC 2004
Portland (OR), USA
June 2004
Congress on Evolutionary Computation, CEC 2004
IEEE Press
2
2152
2158
9780780385153
evolutionary computation; structured population; optimisation
DORRONSORO B; ALBA E; GIACOBINI M; TOMASSINI M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/18124
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