Differential Evolution for Optimization of Land Use

Zhu, Yanjie; Feng, Zuo-Hua

doi:10.1007/978-3-642-13495-1_61

Lecture Notes in Computer Science

2010

DOI: 10.1007/978-3-642-13495-1_61

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Differential Evolution for Optimization of Land Use

Yanjie Zhu

Zuo-Hua Feng

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2015

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“…So far, a series of heuristic or meta-heuristic algorithms have been used for solving resource allocation optimization or spatial optimization problems [19] including Genetic Algorithms [20][21][22][23], Tabu Search [24], Evolutionary Algorithm [25][26][27], Self-Organizing Algorithms [28,29], and Simulated Annealing [30].…”

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Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China

Xiang

2015

Sustainability

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Abstract:As the main feature of land use planning, land use allocation (LUA) optimization is an important means of creating a balance between the land-use supply and demand in a region and promoting the sustainable utilization of land resources. In essence, LUA optimization is a multi-objective optimization problem under the land use supply and demand constraints in a region. In order to obtain a better sustainable multi-objective LUA optimization solution, the present study proposes a LUA model based on the multi-objective artificial immune optimization algorithm (MOAIM-LUA model). The main achievements of the present study are as follows: (a) the land-use supply and demand factors are analyzed and the constraint conditions of LUA optimization problems are constructed based on the analysis framework of the balance between the land use supply and demand; (b) the optimization objectives of LUA optimization problems are defined and modeled using ecosystem service value theory and land rent and price theory; and (c) a multi-objective optimization algorithm is designed for solving multi-objective LUA optimization problems based on the novel immune clonal algorithm (NICA). On the basis of the aforementioned achievements, MOAIM-LUA was applied to a real case study of land-use planning in Anlu County, China. Compared to the current land use situation in Anlu County, optimized LUA solutions offer improvements in the social and ecological objective areas. Compared to the existing models, such as the non-dominated sorting genetic algorithm-II, experimental results demonstrate that the model designed in the present study can obtain better non-dominated solution sets and is superior in terms of algorithm stability.

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confidence: 99%

Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China

Xiang

2015

Sustainability

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Differential Evolution for Optimization of Land Use

Cited by 1 publication

References 4 publications

Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China

Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China

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