Fuzzy Preference Programming Framework for Functional assessment of Subway Networks
The 2019 Canadian Infrastructure report card identified 60% of the subway system to be in a very poor to a poor condition. With multiple assets competing for the limited fund, new methodologies are required to prioritize assets for rehabilitation. The report suggested that adopting an Asset Manageme...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Algorithms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4893/13/9/220 |
| _version_ | 1797554614095052800 |
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| author | Mona Abouhamad Tarek Zayed |
| author_facet | Mona Abouhamad Tarek Zayed |
| author_sort | Mona Abouhamad |
| collection | DOAJ |
| description | The 2019 Canadian Infrastructure report card identified 60% of the subway system to be in a very poor to a poor condition. With multiple assets competing for the limited fund, new methodologies are required to prioritize assets for rehabilitation. The report suggested that adopting an Asset Management Plan would assist municipalities in maintaining and operating infrastructure effectively. ISO 55000 emphasized the importance of risk assessment in assessing the value of an organization’s assets. Subway risk assessment models mainly focus on structural failures with minimum focus on functional failure impacts and network criticality attributes. This research presents two modules to measure the functional failure impacts of a subway network, given financial, social, and operational perspectives, in addition to the station criticality. The model uses the Fuzzy Analytical Network Process with application to Fuzzy Preference Programming to calculate the weights for seven failure impact attributers and seven criticality attributes. Data are collected using questionnaires and unstructured/structured interviews with municipality personnel. The analysis identified social impacts to have the highest score of 38%, followed by operational and financial impacts at 34% and 27.65%, respectively. The subway station criticality revealed station location to have the highest impact at 35%, followed by station nature of use and station characteristics at 30.5% and 31.82%, respectively. When integrated with probability of failure, this model provides a comprehensive risk index to optimize stations for rehabilitation. |
| first_indexed | 2024-03-10T16:34:34Z |
| format | Article |
| id | doaj.art-1563d71b93d9404b94f33f674ddf1e84 |
| institution | Directory Open Access Journal |
| issn | 1999-4893 |
| language | English |
| last_indexed | 2024-03-10T16:34:34Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj.art-1563d71b93d9404b94f33f674ddf1e842023-11-20T12:31:31ZengMDPI AGAlgorithms1999-48932020-09-0113922010.3390/a13090220Fuzzy Preference Programming Framework for Functional assessment of Subway NetworksMona Abouhamad0Tarek Zayed1Construction Management, Structural Engineering Department, Faculty of Engineering, Cairo University, Cairo University Rd., Giza 12613, EgyptDepartment of Building and Real Estate, Hong Kong Polytechnic University, Hong Kong, ChinaThe 2019 Canadian Infrastructure report card identified 60% of the subway system to be in a very poor to a poor condition. With multiple assets competing for the limited fund, new methodologies are required to prioritize assets for rehabilitation. The report suggested that adopting an Asset Management Plan would assist municipalities in maintaining and operating infrastructure effectively. ISO 55000 emphasized the importance of risk assessment in assessing the value of an organization’s assets. Subway risk assessment models mainly focus on structural failures with minimum focus on functional failure impacts and network criticality attributes. This research presents two modules to measure the functional failure impacts of a subway network, given financial, social, and operational perspectives, in addition to the station criticality. The model uses the Fuzzy Analytical Network Process with application to Fuzzy Preference Programming to calculate the weights for seven failure impact attributers and seven criticality attributes. Data are collected using questionnaires and unstructured/structured interviews with municipality personnel. The analysis identified social impacts to have the highest score of 38%, followed by operational and financial impacts at 34% and 27.65%, respectively. The subway station criticality revealed station location to have the highest impact at 35%, followed by station nature of use and station characteristics at 30.5% and 31.82%, respectively. When integrated with probability of failure, this model provides a comprehensive risk index to optimize stations for rehabilitation.https://www.mdpi.com/1999-4893/13/9/220fuzzy ANPfuzzy preference programmingsubway networkimpacts of failureinfrastructure assetscriticality index |
| spellingShingle | Mona Abouhamad Tarek Zayed Fuzzy Preference Programming Framework for Functional assessment of Subway Networks Algorithms fuzzy ANP fuzzy preference programming subway network impacts of failure infrastructure assets criticality index |
| title | Fuzzy Preference Programming Framework for Functional assessment of Subway Networks |
| title_full | Fuzzy Preference Programming Framework for Functional assessment of Subway Networks |
| title_fullStr | Fuzzy Preference Programming Framework for Functional assessment of Subway Networks |
| title_full_unstemmed | Fuzzy Preference Programming Framework for Functional assessment of Subway Networks |
| title_short | Fuzzy Preference Programming Framework for Functional assessment of Subway Networks |
| title_sort | fuzzy preference programming framework for functional assessment of subway networks |
| topic | fuzzy ANP fuzzy preference programming subway network impacts of failure infrastructure assets criticality index |
| url | https://www.mdpi.com/1999-4893/13/9/220 |
| work_keys_str_mv | AT monaabouhamad fuzzypreferenceprogrammingframeworkforfunctionalassessmentofsubwaynetworks AT tarekzayed fuzzypreferenceprogrammingframeworkforfunctionalassessmentofsubwaynetworks |