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This paper discusses about the characteristics of distributed genetic algorithms (DGAs). Among the several types of distributed models of GAs, this paper focuses on a stepping stone population model. The effects of the number of subpopulations, subpopulation immigration rate, and immigration interval on the performance of the DGA are examined. Solving standard mathematical problems and a typical structural optimization problem, it is found that there are several advantages in the stepping stone population model of DGAs: this model is very suitable for parallel computation, and the optimum solutions can be obtained efficiently due to the partitioning of the population.

A Study on Parallel Distributed Genetic Algorithms. (Discussion on a Stepping Stone Population Model of Distributed Genetic Algorithms).