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A hybrid approach to supporting physical-change-based renewal projects selection decisions in high-density city: a case study of Chongqing

相互依存 目标规划 最大化 计算机科学 选择(遗传算法) 模糊逻辑 网络分析法 运筹学 持续性 过程(计算) 新颖性 管理科学 数学优化 工程类 机器学习 人工智能 数学 层次分析法 生物 操作系统 哲学 神学 法学 生态学 政治学
作者
Yizhong Chen,Taozhi Zhuang,Guiwen Liu
出处
期刊:Engineering, Construction and Architectural Management [Emerald Publishing Limited]
卷期号:30 (7): 2879-2903 被引量:4
标识
DOI:10.1108/ecam-01-2022-0028
摘要

Purpose The aims of this paper is to establish an appropriate physical-change-based renewal (PCBR) projects selection mechanism capable of selecting the combination of the PCBR projects that can make up an integrated urban renewal program in high-density cities. Design/methodology/approach The research design follows a sequential integrated methodology that combines the calculation algorithms of Fuzzy Analytic Network Process (Fuzzy-ANP) with Zero-One Goal Programming (ZOGP) to support decisions for the selection of PCBR projects. In the first phase, general criteria for assessing the sustainability performance of PCBR projects were collected from relevant literature. In the second phase, the Fuzzy-ANP was used to identify the priority weights of the candidate projects through clarifying the interdependent degree between the criteria and candidate projects. Finally, ZOGP method was selected as a predetermined number of PCBR projects among candidate projects. Findings The feasibility and effectiveness of this hybrid approach is then verified in a case study of Yuzhong District, Chongqing in China. The results of this study indicate that the integrated method is capable of directing the decision maker toward the best compromising solution of PCBR program that can achieve the maximization of sustainable benefits and allocate limited resources most efficiently. Originality/value The novelty of this paper consists in combining the algorithms of the Fuzzy-ANP method with those of the ZOGP model that serves as an effective analysis tool to address practical decision problems. This is the first hybrid algorithms to make PCBR projects selection decision that reach the maximization of the sustainable benefits, both in economic and socio-environmental terms.

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