High performance genetic algorithm for land use planning

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2013 English Publisher:Elsevier BVJournal:Computers, Environment and Urban Systems, volume 37, pages 45-58 (issn: 0198-9715,

Copyright policy )Funded by:EC | HIPEAC

Authors: Porta J.; Parapar J.; Doallo R.; Rivera F.F.; Sante I.; Crecente R.;

doi: 10.1016/j.compenvurbsys.2012.05.003

handle: 2183/20937

High performance genetic algorithm for land use planning

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Abstract

[Abstract] This study uses genetic algorithms to formulate and develop land use plans. The restrictions to be imposed and the variables to be optimized are selected based on current local and national legal rules and experts’ criteria. Other considerations can easily be incorporated in this approach. Two optimization criteria are applied: land suitability and the shape-regularity of the resulting land use patches. We consider the existing plots as the minimum units for land use allocation. As the number of affected plots can be large, the algorithm execution time is potentially high. The work thus focuses on implementing and analyzing different parallel paradigms: multi-core parallelism, cluster parallelism and the combination of both. Some tests were performed that show the suitability of genetic algorithms to land use planning problems.

Xunta de Galicia; 08SIN011291PR

Xunta de Galicia; 2010/06

Xunta de Galicia; 2010/28

Related Organizations

University of Santiago de Compostela
Spain
University of A Coruña
Spain

Keywords

Parallel programming, Distributed programming, Clusters of multi-core systems, Genetic algorithms, Land use planning, GIS

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