Using Multi-objective Optimization Algorithms to Balance Landscape Design of Historic and Cultural Districts with Urban Development Needs

Urban land-use planning, particularly in historical and cultural districts, requires an impressive balance among various competing social, economic, and environmental considerations. In cities across China, the challenge lies in reconciling the demands of modern urban growth with the preservation of rich historical legacies. The preservation of historic landmarks meets the demands of an expanding urban area and infrastructure that the city faces. To improve land-use planning efforts in these contexts, this research proposes an approach that leverages multi-objective evolutionary algorithms combined with remote sensing techniques, specifically the Strength Pareto Evolutionary Algorithm 2 (SPEA2). The research analyses government plans and expert interviews to identify major objectives of urban growth and cultural preservation. To maximize land-use planning, two multi-objective functions are established, one to reduce impacts on historical and cultural areas and the other to optimize the efficiency of urban growth. The findings indicate that this multi-objective optimization technique can significantly support sustainable land-use planning in Chinese cities, ensuring that development requirements are satisfied without sacrificing the integrity of cultural assets using the parameter multi-objective optimization result and Pareto front visualization which considers cultural significance, economic validity, environmental impact, and also using fitness evaluation over generations. These are recommended for Chinese cities that aim to balance growth with historical preservation and use similar approaches.