TAILIEUCHUNG - Ranking of building maintenance contractors using multi-criteria decision making methods and an artificial neural network model

The purpose of this study is to present a method that can be used to select the contractor in such a way that the response robustness is high and the employed method is the most accurate one among other similar methods. | Ranking of building maintenance contractors using multi-criteria decision making methods and an artificial neural network model International Journal of Data and Network Science 4 2020 245 Contents lists available at GrowingScience International Journal of Data and Network Science homepage ijds Ranking of building maintenance contractors using multi-criteria decision making methods and an artificial neural network model Nima Golghamat Raada and Naser Mollaverdi Isfahanib a Department of Industrial Engineering Amirkabir University of Technology Tehran Iran b Department of Industrial Engineering Isfahan University of Technology Tehran Iran CHRONICLE ABSTRACT Article history Building Maintenance plays an important role throughout the building lifecycle from devising Received September 11 2018 conceptual plans to the end. Due to the high cost of building maintenance and the direct impact Received in revised format Sep- of maintenance effectiveness on the quality of life of building occupants special attention must tember 11 2019 be devoted. One of the most important issues in this field is building maintenance contractor se- Accepted December 12 2019 Available online December 12 lection. This issue becomes even more critical in public buildings such as hospitals offices and 2019 military centers. The purpose of this study is to present a method that can be used to select the Keywords contractor in such a way that the response robustness is high and the employed method is the most Contractor Selection accurate one among other similar methods. To do this the contractors are ranked by 7 multi- MCDM criteria decision-making methods. Then the Spearman correlation coefficients are obtained for ANN each pair of methods. When there is a significant difference between the outcomes of the methods Building the output of each method is compared with the output of the Artificial Neural Network ANN Maintenance model. The method with the least difference with

• Kĩ thuật Viễn thông
• Building maintenance contractor
• Multi criteria decision making methods
• Artificial neural network model
• Artificial Neural Network
• Spearman correlation coefficients
• BMC Musculoskeletal Disorders
• Liverpool elbow score
• Elbow stiffness
• Scoring systems