Migration and replacement policies for preserving diversity in dynamic environments

Abstract

This paper seeks to resolve the difficulties arising from the configuration and fine-tuning of a Parallel Genetic Algorithm (PGA) based on the Island Model, when the application domain is highly dynamic. This way, the reader will find a number of useful guidelines for setting up a PGA in a real, representative dynamic environment. To achieve this purpose, we examine different (existing and new) migration and replacement policies for three different topologies. Of course, there are many other factors that affect the performance of a PGA such as the topology, migrant selection, migration frequency, amount of migrants, replacement policy, number of processing nodes, synchronism type, configuration in the isolated islands, diversity of policies in different islands, etc which are also considered as a part of this study. The pivotal point of all the experiments conducted is the preservation of diversity by means of an appropriate balance between exploration and exploitation in the PGA's search process when the application domain is highly dynamic and strong time constraints arise. The experimental phase is performed over two problem instances from a real-world dynamic environment which is the multi-skill call centre. © 2012 Springer-Verlag.