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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.