Key points are not available for this paper at this time.
• The public determines the contents of the transformation of historical and cultural blocks • The improved NSGA-Ⅱ has a remarkable effect on solving multi-dimensional target problems • merges intelligent optimization algorithms with engineering project management • The equilibrium Pareto solution set of the four-dimensional objective of duration, cost, quality and safety is obtained • pioneers a multi-objective research approach for historical and cultural neighborhoods, filling a notable research void in the area of neighborhood renovation Renovation of historic and cultural districts forms the core of urban renewal initiatives. Unlike traditional engineering projects, renovations in historic and cultural neighborhoods are characterized by their large scale and the involvement of multiple stakeholders, complicating project management. To address these challenges, this study introduces a multi-objective optimization method tailored for renovations in historic and cultural blocks . Specifically applied to Bagua Street in Shenyang, the method seeks to optimize critical objectives, including time, cost, quality, and safety, all while ensuring active public participation. The improved NSGA-II algorithm, which incorporates chaotic mapping and differential mutation strategies, not only improves the convergence speed by 25% but also reduces the computational standard deviation by 30%. When applied to Bagua Street, this approach achieved a reduction in total project duration by 17-49 days and a cost reduction of 10%, without compromising on quality and safety standards. The outcomes of this research offer a multi-dimensional and Pareto-optimal solution set that caters to the diverse needs of various stakeholders, filling a significant gap in the fields of engineering and urban planning by proposing a novel approach to the multi-objective optimization of historic district renovation projects.
Building similarity graph...
Analyzing shared references across papers
Loading...
Jie Ren
Tongji University
Yuxin Zhang
Harbin Engineering University
KSCE Journal of Civil Engineering
Shenyang Jianzhu University
Building similarity graph...
Analyzing shared references across papers
Loading...
Ren et al. (Sun,) studied this question.
synapsesocial.com/papers/69dc57393080d3567e274ef9 — DOI: https://doi.org/10.1016/j.kscej.2025.100214