Asynchronous parallel distributed GA using elite server

Abstract

To speed up GA search, parallel distributed genetic algorithms are used. However in the current asynchronous parallel distributed genetic algorithm like the random-exchange or the sigma-exchange, it is hard to implement on the parallel computers or on the WS/PC clusters on the network, and it is easy to deadlock. We introduce an implementation method for asynchronous parallel distributed genetic algorithm by using the server-client model. In the proposed model, GA is executed on each client and each client communicates to only a server. Therefore, we need not to take care to synchronize between clients. This model is also safety and easy to implement. To evaluate proposed model, we applied to some problems, and confirm the effectiveness.