MULTI-ATTRIBUTE FUZZY WEIGHTED AVERAGE METHOD TO RANK CONSTRUCTION CONTRACTORS

• Published in: Proceedings of the International Annual Conference of the American Society for Engineering Management p. 1
• Main Author: Alhumaidi, Hanouf
• Format: Conference Proceeding
• Language: English
• Published: Huntsville American Society for Engineering Management (ASEM) 01.01.2015
• Subjects: Contractors; Decision making; Fuzzy logic; Fuzzy sets; Linguistics; Pluto; Set theory; Subjectivity; Variables

Contractor selection decision in construction related projects is important and greatly impacts the overall success of any project; therefore, there is a need for quantitative methods to help stakeholders, including owners, make better decisions about contractor selection. Although previous studies have presented different methodologies for contractor selection, the subject of contractor selection remains attractive to many researchers. This study enhances the construction management profession by introducing a new contractor selection method. This paper introduces a quantitative fuzzy-set method to assist in the contractor selection process by implementing multi-attribute decision-making. The method introduced in this research is intended to help decision-makers rank different contractors based on various attributes. The triangular fuzzy-set model is implemented to define the linguistic terms used to describe subjective judgment related to attribute weight assessment and selection attributes rating. This research implements decision-maker's input on beliefs about the importance of a set of attributes that contribute to the decision to prequalify a given contractor using linguistic terms, which are converted into membership functions. The decision-maker rates different contractors (up to 5 contractors) using linguistic terms, which are converted into membership functions that represent the degree to which decision-maker believes a contractor meets the set of criteria important to the selection decision. A case study of contractor ranking is introduced in the study to illustrate the suggested method. The results of this research provide project stakeholders with valuable insights into the contractor selection problem.