Using simulated annealing and spatial goal programming for solving a multi site land use allocation problem

Authors:
Jeroen C. J. H. Aerts;Marjan van Herwijnen;Theodor J. Stewart
Affiliations:
Institute for Environmental Studies, IVM, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands;Institute for Environmental Studies, IVM, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands;Department of Statistical Sciences, University of Cape Town, Rondebosch, South Africa
Venue:
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Year:
2003

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Abstract

Many resource allocation issues, such as land use- or irrigation planning, require input from extensive spatial databases and involve complex decision-making problems. Recent developments in this field focus on the design of allocation plans that utilize mathematical optimization techniques. These techniques, often referred to as multi criteria decision-making (MCDM) techniques, run into numerical problems when faced with the high dimensionality encountered in spatial applications. In this paper, it is demonstrated how both Simulated annealing, a heuristic algorithm, and Goal Programming techniques can be used to solve high-dimensional optimization problems for multi-site land use allocation (MLUA) problems. The optimization models both minimize development costs and maximize spatial compactness of the allocated land use. The method is applied to a case study in The Netherlands.