ABSTRACT
This chapter presents evolutionary algorithms (EAs) with an emphasis on genetic algorithms (GAs) and their ability to search large areas of a solution space for finding optimal parameters. EAs can also be used to build models by breeding model equations. We present the building blocks of EAs followed by a review of EA applications in geography. Two illustrative case studies are then provided which demonstrate how GAs can be applied to find optimal parameters in an agent-based model of retail and in breeding spatial interaction models for use in education. We end with a general discussion on the utility of GAs and, more broadly, EAs in geography and GeoComputation.
