Sustainable land use optimization using Boundary-based Fast Genetic Algorithm
Under the notion of sustainable development, a heuristic method named as the Boundary-based Fast Genetic Algorithm (BFGA) is developed to search for optimal solutions to a land use allocation problem with multiple objectives and constraints. Plans are obtained based on the trade-off among economic b...
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sg-smu-ink.sis_research-64102020-12-11T06:33:18Z Sustainable land use optimization using Boundary-based Fast Genetic Algorithm CAO, Kai HUANG, Bo WANG, Shaowen LIN, Hui Under the notion of sustainable development, a heuristic method named as the Boundary-based Fast Genetic Algorithm (BFGA) is developed to search for optimal solutions to a land use allocation problem with multiple objectives and constraints. Plans are obtained based on the trade-off among economic benefit, environmental and ecological benefit, social equity including Gross Domestic Product (GDP), conversion cost, geological suitability, ecological suitability, accessibility, Not In My Back Yard (NIMBY) influence, compactness, and compatibility. These objectives and constraints are formulated into a Multi-objective Optimization of Land Use (MOLU) model based on a reference point method (i.e. goal programming). This paper demonstrates that the BFGA is effective by offering the possibility of searching over tens of thousands of plans for trade-off sets of non-dominated plans. This paper presents an application of the model to the Tongzhou Newtown in Beijing, China. The results clearly evince the potential of the model in a planning support process by generating suggested near-optimal planning scenarios considering multi-objectives with different preferences. 2012-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5407 https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6410&context=sis_research http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Land use optimization Genetic algorithm Sustainability Spatial compactness Reference point Tongzhou Newtown Databases and Information Systems Theory and Algorithms |
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Land use optimization Genetic algorithm Sustainability Spatial compactness Reference point Tongzhou Newtown Databases and Information Systems Theory and Algorithms CAO, Kai HUANG, Bo WANG, Shaowen LIN, Hui Sustainable land use optimization using Boundary-based Fast Genetic Algorithm |
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Under the notion of sustainable development, a heuristic method named as the Boundary-based Fast Genetic Algorithm (BFGA) is developed to search for optimal solutions to a land use allocation problem with multiple objectives and constraints. Plans are obtained based on the trade-off among economic benefit, environmental and ecological benefit, social equity including Gross Domestic Product (GDP), conversion cost, geological suitability, ecological suitability, accessibility, Not In My Back Yard (NIMBY) influence, compactness, and compatibility. These objectives and constraints are formulated into a Multi-objective Optimization of Land Use (MOLU) model based on a reference point method (i.e. goal programming). This paper demonstrates that the BFGA is effective by offering the possibility of searching over tens of thousands of plans for trade-off sets of non-dominated plans. This paper presents an application of the model to the Tongzhou Newtown in Beijing, China. The results clearly evince the potential of the model in a planning support process by generating suggested near-optimal planning scenarios considering multi-objectives with different preferences. |
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CAO, Kai HUANG, Bo WANG, Shaowen LIN, Hui |
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CAO, Kai HUANG, Bo WANG, Shaowen LIN, Hui |
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CAO, Kai |
title |
Sustainable land use optimization using Boundary-based Fast Genetic Algorithm |
title_short |
Sustainable land use optimization using Boundary-based Fast Genetic Algorithm |
title_full |
Sustainable land use optimization using Boundary-based Fast Genetic Algorithm |
title_fullStr |
Sustainable land use optimization using Boundary-based Fast Genetic Algorithm |
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Sustainable land use optimization using Boundary-based Fast Genetic Algorithm |
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sustainable land use optimization using boundary-based fast genetic algorithm |
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Institutional Knowledge at Singapore Management University |
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2012 |
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https://ink.library.smu.edu.sg/sis_research/5407 https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6410&context=sis_research |
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