Spatial multi-objective land use optimization: extensions to the nondominated sorting genetic algorithm-II

Cao, Kai, Batty, Michael, Huang, Bo, Liu, Yan, Yu, Le and Chen, Jiongfeng (2011) Spatial multi-objective land use optimization: extensions to the nondominated sorting genetic algorithm-II. International Journal of Geographical Information Science, 25 12: 1949-1969. doi:10.1080/13658816.2011.570269

Author Cao, Kai
Batty, Michael
Huang, Bo
Liu, Yan
Yu, Le
Chen, Jiongfeng
Title Spatial multi-objective land use optimization: extensions to the nondominated sorting genetic algorithm-II
Journal name International Journal of Geographical Information Science   Check publisher's open access policy
ISSN 1362-3087
Publication date 2011-12-01
Sub-type Article (original research)
DOI 10.1080/13658816.2011.570269
Volume 25
Issue 12
Start page 1949
End page 1969
Total pages 21
Place of publication Colchester, Essex, United Kingdom
Publisher Taylor & Francis
Language eng
Abstract A spatial multi-objective land use optimization model defined by the acronym ‘NSGA-II-MOLU’ or the ‘non-dominated sorting genetic algorithm-II for multi-objective optimization of land use’ is proposed for searching for optimal land use scenarios which embrace multiple objectives and constraints extracted from the requirements of users, as well as providing support to the land use planning process. In this application, we took the MOLU model which was initially developed to integrate multiple objectives and coupled this with a revised version of the genetic algorithm NSGA-II which is based on specific crossover and mutation operators. The resulting NSGA-II-MOLU model is able to offer the possibility of efficiently searching over tens of thousands of solutions for trade-off sets which define non-dominated plans on the classical Pareto frontier. In this application, we chose the example of Tongzhou New Town, China, to demonstrate how the model could be employed to meet three conflicting objectives based on minimizing conversion costs, maximizing accessibility, and maximizing compatibilities between land uses. Our case study clearly shows the ability of the model to generate diversified land use planning scenarios which form the core of a land use planning support system. It also demonstrates the potential of the model to consider more complicated spatial objectives and variables with open-ended characteristics. The breakthroughs in spatial optimization that this model provides lead directly to other properties of the process in which further efficiencies in the process of optimization, more vivid visualizations, and more interactive planning support are possible. These form directions for future research.
Keyword Spatial land use optimization
Planning support systems
Land use planning
Multi-objective optimization
Tongzhou New Town
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
Official 2012 Collection
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Citation counts: TR Web of Science Citation Count  Cited 45 times in Thomson Reuters Web of Science Article | Citations
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Created: Thu, 08 Dec 2011, 05:49:13 EST by Dr Yan Liu on behalf of School of Geography, Planning & Env Management