Dynamic Demes parallel genetic algorithm

Abstract—Dynamic Demes is a new method for the parallelisation of evolutionary algorithms. It was derived as a combination of two other parallelisation algorithms: the master-slave distributed fitness evaluation model and the static subpopulation model. In this paper we present the algorithm, perform a theoretical analysis of its performance and present experimental results where we compared Dynamic Demes with other algorithms. I. PARALLEL GENETIC ALGORITHMS Sequential GAs have been shown to be very successful in many applications and in very different domains. However, there exist some problems in their utilisation which can all be addressed with some form of Parallel GA (PGA):   For some kind of problems, the population needs to be very large and the memory required to store each individual may be considerable (for example in genetic programming [1]). In some cases this makes it impossible to run an application efficiently using a single machine, so some parallel form of GA is n...

• Type: Conference
• Year: 1999
• Where: KES
• Authors: Mariusz Nowostawski, Riccardo Poli
• Keywords: ALGORITHMS Sequential GAs, Information Management, KES 1999, Master-slave Distributed fitness, Sequential GAs