Experiences with fine-grained parallel genetic algorithms

In this paper, we present some results of our systematic studies of fine-grained parallel versions of the island model of genetic algorithms and of variants of the neighborhood model (also called diffusion model) on the massively parallel computer MasPar MP1 with 16k processing elements. These parallel genetic algorithms have been applied to a range of different problems (e.g. traveling salesman, capacitated lot sizing, resource-constrained project scheduling, flow shop, and warehouse location problems) in order to obtain an empirical basis for statements on their optimization quality.