Assessment of Airport Pavement Sustainability Using an Integrated Fuzzy ANP-TOPSIS Decision Model

Sustainable design is the future of heavy construction projects such as airports. However, these structures usually require constant maintenance, which can become a major financial burden. The maintenance and rehabilitation of pavement, especially at airports, is a costly process which includes labour, equipment, and material expenses. By transitioning to a system that uses more sustainable designs and building materials, it is possible to build better structures that will not suffer serious damage. This research aims at building a new assessment framework for sustainable air-port pavements to be later applied to the case study of Taif airport in Saudi Arabia. To assess the proposed international airport in terms of sustainability, four sustainable alternatives (A1, A2, A3, and A4) are proposed, along with nine criteria. These alternatives are studied and the TOPSIS method is used to select the best alternative. Additionally, weights are calculated using the Fuzzy Analytic Network Process (FANP). According to achieved results, the best alternative is A4 (pavement made with recycled materials). This eco-friendly solution is recommended to the local Saudi authority as the optimal material to be used in the construction of the new Taif airport by including sustainability factors into the design process, allowing for informed judgements. Enhances airport pavement design processes and decrease environmental impacts connected with airport operations in a variety of contexts and locations. However, it can be concluded that the key findings of this study could provide a robust framework for optimizing sustainability in airport pavement management, enhancing decision-making efficiency and promoting long-term environmental, economic, and operational benefits.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.63070/jesc.2024.014
Primary Topic
Multi-Criteria Decision Making
Type
article
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article

Assessment of Airport Pavement Sustainability Using an Integrated Fuzzy ANP-TOPSIS Decision Model

Badr T. Alsulami
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Multi-Criteria Decision Making
article

Assessment of Airport Pavement Sustainability Using an Integrated Fuzzy ANP-TOPSIS Decision Model

Badr T. Alsulami
article en

Abstract

Sustainable design is the future of heavy construction projects such as airports. However, these structures usually require constant maintenance, which can become a major financial burden. The maintenance and rehabilitation of pavement, especially at airports, is a costly process which includes labour, equipment, and material expenses. By transitioning to a system that uses more sustainable designs and building materials, it is possible to build better structures that will not suffer serious damage. This research aims at building a new assessment framework for sustainable air-port pavements to be later applied to the case study of Taif airport in Saudi Arabia. To assess the proposed international airport in terms of sustainability, four sustainable alternatives (A1, A2, A3, and A4) are proposed, along with nine criteria. These alternatives are studied and the TOPSIS method is used to select the best alternative. Additionally, weights are calculated using the Fuzzy Analytic Network Process (FANP). According to achieved results, the best alternative is A4 (pavement made with recycled materials). This eco-friendly solution is recommended to the local Saudi authority as the optimal material to be used in the construction of the new Taif airport by including sustainability factors into the design process, allowing for informed judgements. Enhances airport pavement design processes and decrease environmental impacts connected with airport operations in a variety of contexts and locations. However, it can be concluded that the key findings of this study could provide a robust framework for optimizing sustainability in airport pavement management, enhancing decision-making efficiency and promoting long-term environmental, economic, and operational benefits.

Vol. VI(II)
Openalex Percentile: Top 64%
Multi-Criteria Decision Making
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