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Project delivery system selection under uncertainty: multicriteria multilevel decision aid model

Project delivery system selection under uncertainty: multicriteria multilevel decision aid model

Mafakheri, Fereshteh, Dai, Liming, Slezak, Dominik and Nasiri, Fuzhan (2007) Project delivery system selection under uncertainty: multicriteria multilevel decision aid model. Journal of Management in Engineering, 23 (4). pp. 200-206. ISSN 0742-597X (Print), 1943-5479 (Online) (doi:10.1061/(ASCE)0742-597X(2007)23:4(200))

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Abstract

Selecting an optimal project delivery system is a critical task that owners should do to ensure project success. This selection is a complex decision-making process. The complexity arises from the uncertain or not well-defined parameters and/or the multiple criteria structure of such decisions. In this study, a decision aid model using the analytical hierarchy process (AHP) coupled with rough approximation concepts is developed to assist the owners. The selection criteria are determined by studying a number of benchmarks. The model ranks the alternative delivery systems by considering both benchmark results and owner’s opinion. In interval AHP, an optimization procedure is performed via obtaining the upper and the lower linear programming models to determine the interval priorities for alternative project delivery systems. In cases having incomparable alternatives, which is the most likely case in uncertain decision making, the model uses rough set-based measures to reduce the number of decision criteria to a subset, which is able to fully rank the alternatives. To illustrate the applicability and usefulness of this methodology, a real world case study will be demonstrated.

Item Type: Article
Uncontrolled Keywords: project management, contract management, delivery, decision support systems, approximation methods, multiple objective analysis, uncertainty principles
Subjects: H Social Sciences > HD Industries. Land use. Labor
Faculty / Department / Research Group: Faculty of Business > Department of Systems Management & Strategy
Faculty of Business
Related URLs:
Last Modified: 14 Oct 2016 09:16
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/6393

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