An improved Genetic Algorithm for spatial optimization of multi-objective and multi-site land use allocation

Abstract As a result of multiple land use types, spatial heterogeneity, and conflicts of interest among multiple participants, multi-site land use allocation becomes a complex and significant optimization issue. We propose an improved Genetic Algorithm (GA) to deal with multi-site land use allocation, in which maximum economic benefit, maximum ecological benefit, maximum suitability, and maximum compactness were formulated as optimal objectives; and residential space demand and some regulatory knowledge were set as constraints. A Goal Programming model with a reference point form was used to manage trade-offs among multiple objectives. In order to improve the efficiency of the common GA applied to multi-site land use allocation, two crossover steps and two mutation operations were designed. This paper presents an application of the improved GA to the Regional District of Central Okanagan in Canada. Results showed that the proposed GA exhibited good robustness and could generate any optimal land use scenario according to stakeholders' preferred objectives, thus having the potential to provide interactive technical support for land use planning.

[1]  B. Eickhout,et al.  A multi-scale, multi-model approach for analyzing the future dynamics of European land use , 2008 .

[2]  Theodor J. Stewart,et al.  Use of piecewise linear value functions in interactive multicriteria decision support: a Monte Carlo study , 1993 .

[3]  Theodor J. Stewart,et al.  A genetic algorithm approach to multiobjective land use planning , 2004, Comput. Oper. Res..

[4]  J. McLaughlin.  Urban Land Use Planning, 5th ed., P.R. Berke, D.R. Godschalk, E.J. Kaiser, D.A. Rodriguez. University of Illinois Press, Champaign, IL (2006), US$ 75.00, Hardback, ISBN: 9780252030796 , 2009 .

[5]  Jean-Marie Lescot,et al.  Comparison of Two Spatial Optimization Techniques: A Framework to Solve Multiobjective Land Use Distribution Problems , 2009, Environmental management.

[6]  Yaolin Liu,et al.  Regional land-use allocation with a spatially explicit genetic algorithm , 2014, Landscape and Ecological Engineering.

[7]  Inés Santé-Riveira,et al.  Algorithm based on simulated annealing for land-use allocation , 2008, Comput. Geosci..

[8]  S. Carpenter,et al.  Global Consequences of Land Use , 2005, Science.

[9]  Eastman J. Ronald,et al.  RASTER PROCEDURES FOR MULTI-CRITERIA/MULTI-OBJECTIVE DECISIONS , 1995 .

[10]  Xiaoping Liu,et al.  Intelligent GIS for solving high‐dimensional site selection problems using ant colony optimization techniques , 2009, Int. J. Geogr. Inf. Sci..

[11]  Yaolin Liu,et al.  Regional land-use allocation using a coupled MAS and GA model: from local simulation to global optimization, a case study in Caidian District, Wuhan, China , 2014 .

[12]  Shaowen Wang,et al.  Sustainable land use optimization using Boundary-based Fast Genetic Algorithm , 2012, Comput. Environ. Urban Syst..

[13]  Daniel G. Brown,et al.  Knowledge-informed Pareto simulated annealing for multi-objective spatial allocation , 2007, Comput. Environ. Urban Syst..

[14]  Richard L. Church,et al.  Spatial optimization as a generative technique for sustainable multiobjective land‐use allocation , 2008, Int. J. Geogr. Inf. Sci..

[15]  Xiaoping Liu,et al.  A multi-type ant colony optimization (MACO) method for optimal land use allocation in large areas , 2012, Int. J. Geogr. Inf. Sci..

[16]  Ron Janssen,et al.  Evaluating Spatial Design Techniques for Solving Land-use Allocation Problems , 2005 .

[17]  Claire A. Montgomery,et al.  Where to put things? Spatial land management to sustain biodiversity and economic returns , 2008 .

[18]  Demetris Demetriou,et al.  A spatial genetic algorithm for automating land partitioning , 2013, Int. J. Geogr. Inf. Sci..

[19]  Luis A. Bojórquez-Tapia,et al.  Multivariate approach for suitability assessment and environmental conflict resolution , 1994 .

[20]  P. Sutton,et al.  Changes in the global value of ecosystem services , 2014 .

[21]  Yu Yan,et al.  Model of urban land-use spatial optimization based on particle swarm optimization algorithm. , 2010 .

[22]  G. Heuvelink,et al.  Using Linear Integer Programming for Multi-Site Land-Use Allocation , 2003 .

[23]  K. D. Cocks,et al.  Using mathematical programming to address the multiple reserve selection problem: An example from the Eyre Peninsula, South Australia , 1989 .

[24]  T. Stewart,et al.  A multiobjective GIS-based land use planning algorithm , 2014, Comput. Environ. Urban Syst..

[25]  Theodor J. Stewart,et al.  A Multi-criteria Decision Support System for R&D Project Selection , 1991 .

[26]  Ron Janssen,et al.  Spatial decision support for collaborative land use planning workshops , 2012 .

[27]  G. J. Carsjens,et al.  Strategic land use allocation : dealing with spatial relationships and fragmentation of agriculture , 2002 .

[28]  Xia Li,et al.  Combining system dynamics and hybrid particle swarm optimization for land use allocation , 2013 .

[29]  Francisco F. Rivera,et al.  High performance genetic algorithm for land use planning , 2013, Comput. Environ. Urban Syst..

[30]  H. Jianhua,et al.  Rural land use spatial allocation in the semiarid loess hilly area in China: Using a Particle Swarm Optimization model equipped with multi-objective optimization techniques , 2012 .

[31]  S. Polasky,et al.  CONSERVING SPECIES IN A WORKING LANDSCAPE: LAND USE WITH BIOLOGICAL AND ECONOMIC OBJECTIVES , 2005 .

[32]  Yanfang Liu,et al.  A Land-use Spatial Allocation Model Based on Modified Ant Colony Optimization , 2014 .

[33]  John Stillwell,et al.  Planning Support Systems: Content, Issues and Trends , 2009 .

[34]  Gerard B. M. Heuvelink,et al.  Using simulated annealing for resource allocation , 2002, Int. J. Geogr. Inf. Sci..

[35]  Cheng-Min Feng,et al.  Using a genetic algorithm to generate alternative sketch maps for urban planning , 1999 .

[36]  Ron Janssen,et al.  Multiobjective Decision Support for Land-Use Planning , 2008 .

[37]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[38]  J. Radke,et al.  An Application of Linear Programming and Geographic Information Systems: Cropland Allocation in Antigua , 1992 .

[39]  Stephen J. Carver,et al.  Integrating multi-criteria evaluation with geographical information systems , 1991, Int. J. Geogr. Inf. Sci..

[40]  Seyed Hamidreza Sadeghi,et al.  Land use optimization in watershed scale , 2009 .

[41]  Susan Craw,et al.  Applying Genetic Algorithms to Multi-Objective Land Use Planning , 2000, GECCO.

[42]  Christopher J. Brookes.  A genetic algorithm for locating optimal sites on raster suitability maps , 1997, Trans. GIS.

[43]  Ilkka Hanski,et al.  Metapopulation dynamics and conservation: A spatially explicit model applied to butterflies , 1994 .

[44]  David A. Bennett,et al.  Interactive evolutionary approaches to multiobjective spatial decision making: A synthetic review , 2007, Comput. Environ. Urban Syst..

[45]  Richard J. Balling,et al.  Multiobjective Urban Planning Using Genetic Algorithm , 1999 .

[46]  David A. Bennett,et al.  Using Evolutionary Algorithms to Generate Alternatives for Multiobjective Site-Search Problems , 2002 .

[47]  Christopher J. Brookes,et al.  A Parameterized Region-Growing Programme for Site Allocation on Raster Suitability Maps , 1997, Int. J. Geogr. Inf. Sci..

[48]  Christopher J. Brookes,et al.  A genetic algorithm for designing optimal patch configurations in GIS , 2001, Int. J. Geogr. Inf. Sci..

[49]  R Sharpe,et al.  Urban land use planning , 1988 .

[50]  Liu Yanfang,et al.  Land use structure optimization under systematic framework , 2002 .

[51]  Paul Schot,et al.  Land use change modelling: current practice and research priorities , 2004 .

[52]  T. Stewart.  Robustness of Additive Value Function Methods in MCDM , 1996 .

[53]  YaoLin Liu,et al.  Rural land use spatial allocation in the semiarid loess hilly area in China: Using a Particle Swarm Optimization model equipped with multi-objective optimization techniques , 2012, Science China Earth Sciences.