相互依存
文件夹
选择(遗传算法)
持续性
项目组合管理
帕累托原理
环境经济学
适应性
资源(消歧)
风险分析(工程)
计算机科学
业务
项目管理
工程类
经济
运营管理
系统工程
生物
计算机网络
人工智能
生态学
管理
法学
政治学
财务
作者
Yizhong Chen,Guiwen Liu,Taozhi Zhuang
标识
DOI:10.1016/j.eiar.2023.107283
摘要
Urban regeneration is a crucial approach in addressing urban decay and improving the urban living environment. However, the viability of urban regeneration projects (URP) is largely determined by their investment value. This makes it challenging to promote non- or low-profitable URP in many cases. Lacking sufficient market value, such projects tend to rely heavily on limited public resources, which can be a significant burden on society. To address this issue, it is necessary to establish an appropriate area-wide project portfolio selection approach to comprehensively plan and implement URP. Previous studies have focused on single project scales and failed to consider project interdependencies and the multiple objectives of URP. Therefore, this study develops a multi-objective optimization approach for URP portfolio selection that integrates project interdependencies and multiple objectives into a comprehensive mathematical model. The NSGA-II and the TOPSIS are used to obtain trade-off solutions from the Pareto-optimal set. The approach is utilized to a case of Chongqing, China, showcasing its effectiveness in guiding decision-makers towards an optimal URP portfolio that maximizes sustainable benefits. This approach provides new insights into the balance between functional adaptability, resource sustainability, and land utilization efficiency in urban built-up areas.
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