多目标遗传算法与类型学导向的历史街区更新OACHSSCD

To address the conflicts between cultural continuity and contemporary functional demands in the renewal of historic blocks under fragmented property ownership,the Northwest Area of Mengzi Ancient City was chosen to investigate the feasibility and optimization strategies of integrating morphological typology with a multi-objective genetic algorithm in the renewal of historic blocks.In this study,the property boundaries were first determined through field investigation and literature analysis,and the operable core land use was identified.Based on the Conzenian principles of"property plot plan unit-land use",the core plot was further consolidated into several optimization clusters,forming basic units for parametric optimization.Based on typological analysis,three representative spatial patterns of courtyard-based enclosed texture,linear texture along the main street,and fragmented texture were identified.Key preservation and renewal rules are extracted for each pattern to serve as constraints for subsequent multi-objective optimization. Methodologically,the rules derived from morphological typology are translated into variables,constraints,and objectives that the multi-objective genetic algorithm can recognize.Building height and building setback were defined as the core genetic variables,while the principal optimization goals were set to minimize floor area ratio and building density and maximize building volume.Parametric modeling and iterative computation were conducted using the Grasshopper-Wallacei platform to generate a Pareto-optimal solution set.Candidate solutions were subsequently compared and screened using a weighted comprehensive evaluation method,supported by parallel coordinate plots and standard deviation diagrams,to select the optimal scheme.This approach establishes a technical route of"rule extraction—parameter translation—scheme generation—design refinement",enabling the renewal of historical blocks to shift from experience-based judgment to a framework integrating qualitative and quantitative analyses. For performance verification,the optimized results were assessed across five dimensions:development intensity,spatial openness,continuity of historical context,spatial resilience,and livability.The findings indicate that while controlling development intensity,the optimized scheme improves overall spatial organization,releases courtyard and small-scale public spaces,enhances the continuity of street interfaces and the preservation of historic alley scales,and significantly improves evacuation accessibility,fire protection coverage,open-space allocation,and public-space availability.These results demonstrate that spatial prototypes derived from morphological typology can be effectively incorporated into the optimization process via parameter translation,while the multi-objective genetic algorithm balances historical continuity,spatial resilience,and livability across multiple constraints. Based on the algorithmic optimization results and subsequent design interventions,further strategies were proposed to enhance both the feasibility and completeness of the scheme;these included a multi-level park,a parking system,elevated corridors,adjustments to the road network,and fire protection enhancements.Generally speaking,integrating morphological typology with a multi-objective genetic algorithm not only provides quantitative solutions for the renewal of property-fragmented historical blocks and supports the comparison and selection of schemes,but also offers technical approaches and practical references for balancing cultural preservation,spatial optimization,and functional adaptation of similar historical blocks.