Hybrid Fuzzy Sustainability Assessment Model: A Case Study of a Regional Infrastructure Transport Project

Alsulami, Badr T.; Mohamed, Sherif Ali Mohtady

doi:10.1061/9780784412688.048

Cited by 5 publications

(4 citation statements)

References 9 publications

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“…For example, Govindan et al () introduced a fuzzy multicriterion approach to measure the sustainability performance of suppliers. Alsulami and Mohamed () presented an innovative model, which combined fuzzy‐set theory and fuzzy cognitive maps to assess the sustainability performance of infrastructure. Phillis et al () developed a SAFE model for sustainability assessment, which contains 75 indicators to evaluate the sustainability performance of 128 selected countries.…”

Section: Literature Reviewmentioning

confidence: 99%

“…For example, Govindan et al (2013) introduced a fuzzy multicriterion approach to measure the sustainability performance of suppliers. Alsulami and Mohamed (2014) Sustainability assessment is a complex, multicriterion and dynamic process, which involves various nonlinear relationships between variables (Hjorth & Bagheri, 2006;López-Ridaura, Masera, & Astier, 2002). Therefore, predefined fuzzy rules and linear membership functions may not reflect the real rules and membership distributions (Buragohain & Mahanta, 2008;Naderloo et al, 2012).…”

Section: Literature Reviewmentioning

confidence: 99%

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Adaptive neuro‐fuzzy inference system approach for urban sustainability assessment: A China case study

Tan

Shuai

Jiao

et al. 2018

Sustainable Development

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Urbanization, especially in developing countries, has led to numerous concerns, such as air pollution, traffic congestion and habitat destruction. Within this context, it is important to evaluate urban development as sustainable, and various sustainability assessment methods have been developed, including fuzzy logic approaches. However, predefined fuzzy rules and simple linear membership functions were used, which are largely based on the knowledge of subject experts. Therefore, this paper aims to introduce an adaptive neuro‐fuzzy inference systems (ANFIS) approach for urban sustainability assessment. With collected training samples from the Urban China Initiative, and the ANFIS approach was used to rank 185 selected cities in China. The results show that the ANFIS approach is appropriate for assessing urban sustainability, and the nonlinear membership functions fit the training samples better than the linear membership functions. Further discussion indicates that future research on sustainability assessment should be more integrated.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Adaptive neuro‐fuzzy inference system approach for urban sustainability assessment: A China case study

Tan

Shuai

Jiao

et al. 2018

Sustainable Development

View full text Add to dashboard Cite

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“…Nevertheless, these influences are often vague and uncertain and sometimes information is incomplete. To satisfy these issues, fuzzy set theory can be applied (Andriantiatsaholiniaina et al 2004;Alsulami, Mohamed 2012;Tseng 2013) and integrated into assessment methods (Phillis, Andriantiatsaholiniaina 2001;Pislaru, Trandabat 2012).…”

Section: Sustainability Measures and Dependenciesmentioning

confidence: 99%

Sustainability Index With Integrated Indicator Dependencies

Wagenhals

Garner

Duckers

et al. 2014

Business, Management and Education

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Sustainability is a growing concern worldwide. While companies used to focus on financial performance, now the focus has shifted to considering envi- ronmental and social performance as well. This trend is not only based on ‘image’, but recent research has proven that a complex approach regarding sustainability could significantly increase a company’s performance. The selection of sustainability indicators as well as the development of sustainabil- ity frameworks has been analysed by researchers already. The authors argue that interdependencies exist between different sustainability indicators and concepts. To address this issue, the fuzzy set method has been used and integrated into as- sessment methods, making it possible to develop a sustainability index which is able to consider the dependencies of the integrated variables. The proposed method can prove that indicator dependencies have a significant influence on the sustain - ability performance of a company and therefore on its overall performance.

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“…Other studies only analyse the cost components associated with sustainability indicators during project evaluation [10]. Though some studies incorporate indicators from three areas (economic, social and environmental) of sustainability, their assessment approaches lack consideration of the conflicting and dynamic nature of indicators at different project lifecycle phases [11,12]. Certain studies concentrate more on analytically comparing sustainability-related (GHG(CO 2 -eq) emissions, fatality rate, economic costs, noise emis-sions abatement) performance analysis of roundabouts and intersections [13,14].…”

mentioning

confidence: 99%

An Integrated DPSIR-SD Framework for Sustainability Assessment of Roads in Australia

et al. 2022

Self Cite

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The Australian Sustainability Development Goals (SDGs) Summit in 2018 attracted much-needed national attention towards environmental goals and targets compared with other aspects of sustainability. Road infrastructure is the backbone of modern society and plays a crucial role in accomplishing a targeted balance between these aspects of sustainability and achieving the SDGs. This article presents an integrated sustainability performance assessment methodology that acts as a decision support tool. A series of two conceptual modelling techniques—drivers—pressure—state—impact—response (DPSIR) and system dynamics (SD)—is employed, with the cause-and-effect relationships of the sustainability indicators developed utilising the DPSIR framework, and a quantitative analysis carried out through a subsequent SD model. The end result is the generation of a Sustainability Performance Index (SPI) for road infrastructure created by analysing the SD model and DPSIR index layer relationship. The benefits and applicability of the proposed methodology are validated through case study analysis. The overall aim is to determine restricting factors and response strategies influencing road infrastructure and transport sustainability performance during the operation and maintenance phase. Thus, a significant contribution is made through the proposed methodology for assessing factors influencing the long-term achievement of the SDGs.

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Hybrid Fuzzy Sustainability Assessment Model: A Case Study of a Regional Infrastructure Transport Project

Cited by 5 publications

References 9 publications

Adaptive neuro‐fuzzy inference system approach for urban sustainability assessment: A China case study

Adaptive neuro‐fuzzy inference system approach for urban sustainability assessment: A China case study

Sustainability Index With Integrated Indicator Dependencies

An Integrated DPSIR-SD Framework for Sustainability Assessment of Roads in Australia

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