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Application of Type-2 Interval Fuzzy Sets to Contractor Qualification Process
Abstract The selection of a general contractor for construction works is one of the most important decisions made throughout the entire construction project. It may be decisive in the success or failure of the project (e.g. delays in the commissioning of works, exceeding the budget, low quality of works). The article presents a method for supporting group decision-making in the contractor qualification process. The proposed method is a development of Mikhailov’s approach to Fuzzy Analytic Hierarchy Process. It consists in the aggregation of the decision makers’ judgments using type-2 fuzzy sets, allowing for inaccuracy of the decision-maker’s assessment. The use of an unbiased estimator of standard deviation for determining compromise evaluation enables the small size of the expert group and deviations in their evaluations to be taken into consideration. The quality of the solution obtained through this method was compared with the results obtained by means of Mikhailov’s Fuzzy Preference Programming and Enea & Piazza Method. The use of the proposed method generated better results for this example of preparing a ranking of contractors than the two other methods discussed. The method presented herein may also be proposed for solving decision-making problems in other spheres.
Application of Type-2 Interval Fuzzy Sets to Contractor Qualification Process
Abstract The selection of a general contractor for construction works is one of the most important decisions made throughout the entire construction project. It may be decisive in the success or failure of the project (e.g. delays in the commissioning of works, exceeding the budget, low quality of works). The article presents a method for supporting group decision-making in the contractor qualification process. The proposed method is a development of Mikhailov’s approach to Fuzzy Analytic Hierarchy Process. It consists in the aggregation of the decision makers’ judgments using type-2 fuzzy sets, allowing for inaccuracy of the decision-maker’s assessment. The use of an unbiased estimator of standard deviation for determining compromise evaluation enables the small size of the expert group and deviations in their evaluations to be taken into consideration. The quality of the solution obtained through this method was compared with the results obtained by means of Mikhailov’s Fuzzy Preference Programming and Enea & Piazza Method. The use of the proposed method generated better results for this example of preparing a ranking of contractors than the two other methods discussed. The method presented herein may also be proposed for solving decision-making problems in other spheres.
Application of Type-2 Interval Fuzzy Sets to Contractor Qualification Process
Tomczak, Michał (author) / Jaśkowski, Piotr (author)
KSCE Journal of Civil Engineering ; 22 ; 2702-2713
2018-01-08
12 pages
Article (Journal)
Electronic Resource
English
Application of Type-2 Interval Fuzzy Sets to Contractor Qualification Process
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