Evolutionary computing for optimizing a region’s distribution of agricultural productionCreated by Ray Wyatt & Hemayet Hossain
This paper describes a GIS-based software package that incorporates a ‘genetic algorithm’ to optimize crops’ distribution across any region. Such optimization is powered by maps of where one finds the most suitable conditions for each crop, or each crop’s current local yields, market price, market demand or transport costs. Our program’s output is the crops distribution which achieves maximum economic return, or minimal environmental damage, or optimal fit with either present- or post-climatic-change soil suitability or minimum transport cost. The package can be implemented within any region where the necessary input data exists in Ascii and image format, and it incorporates a number of features that make it transparent and flexible. Such user friendliness encourages even laypersons to experiment with the genetic algorithm’s parameters, almost as if they are playing a computer game, to see whether or not they can find an even more optimal crops distribution than they found previously. The package also functions as a useful exploratory tool for seeing how current patterns would have to be modified if a more optimal crops distribution were achieved, thereby generating decision support type insights into possible repercussions of tampering with the status quo. Our package’s functionality will be demonstrated through a case study implementation within the agricultural region of South Gippsland, Australia.