Renovation and Reconstruction of Urban Land Use by a Cost-Heuristic Genetic Algorithm: A Case in Shenzhen

• Published in: ISPRS international journal of geo-information Vol. 13; no. 7; p. 250
• Main Authors: Deng, Yufan, Tang, Zhongan, Liu, Baoju, Shi, Yan, Deng, Min, Liu, Enbo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2024
• Subjects: Algorithms; Analysis; Case studies; China; Cities; cost-heuristic genetic algorithm; Costs; Economic aspects; Economic benefits; Economic development; Economics; Efficiency; Game theory; Genetic algorithms; Genetic research; Heuristic; Land resources; Land use; Land use management; Land use planning; Linear programming; multi-objective optimization; Multiple objective analysis; Objectives; Optimization; Optimization models; Population density; probability; Problem solving; Reconstruction; Redevelopment; renovation; Renovation & restoration; Research methodology; system optimization; Urban areas; Urban development; Urban land use; Urban planning; China; Shenzhen China
• ISSN: 2220-9964; 2220-9964
• DOI: 10.3390/ijgi13070250

Urban land use multi-objective optimization aims to achieve greater economic, social, and environmental benefits by the rational allocation and planning of urban land resources in space. However, not only land use reconstruction, but renovation, which has been neglected in most studies, is the main optimization direction of urban land use. Meanwhile, urban land use optimization is subject to cost constraints, so as to obtain a more practical optimization scheme. Thus, this paper evaluated the renovation and reconstruction costs of urban land use and proposed a cost-heuristic genetic algorithm (CHGA). The algorithm determined the selection probability of candidate optimization cells by considering the renovation and reconstruction costs of urban land and integrated the renovation and reconstruction costs to determine the direction of optimization so that the optimization model can more practically simulate the actual situation of urban planning. The reliability of this model was validated through its application in Shenzhen, China, demonstrating that it can reduce the cost consumption of the optimization process by 35.86% at the expense of sacrificing a small amount of economic benefits (1.18%). The balance of benefits and costs enhances the applicability of the proposed land use optimization method in mature, developed areas where it is difficult to demolish buildings that are constrained by costs.