Construction contractors ranking method using multiple decision-makers and multiattribute fuzzy weighted average

The contractor selection decision 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 paper enhances the construction management profession by introducing a new contractor selection method that incorporates multiple decision-makers. This paper introduces a quantitative fuzzy-set method to assist in the contractor selection process by implementing multiattribute decision-making that integrates a group of decision makers. Although the preferred attributes that contribute to contractor selection are dependent on the project, the method presented in this paper can be implemented for any attributes determined important to contractor selection in a specific case. The method introduced in the research reported in this paper 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 decision makers' experience level, attribute weight assessment, and selection attributes rating. Many uncertainties and ambiguities arise in contractor selection as this decision is a multiattribute group decision with time pressure; therefore, the fuzzy weighted-average method can be used to simulate the grouping of multiple decision-makers. The research reported in this paper models different levels of experience for decision makers involved in the evaluation process (up to 10 decision-makers) using fuzzy membership functions to express their experience level. Different decision-makers input their 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 makers rate different contractors (up to five contractors) using linguistic terms, which are converted into membership functions that represent the degree to which decision makers believe a contractor meets the set of criteria important to the prequalification decision. The results of the research reported in this paper provide project stakeholders with valuable insights into the contractor selection problem. A computer program which uses the fuzzy-logic approach to modeling the multiattribute decision-making process is introduced. This program can be implemented by stakeholders to make better contractor-selection decisions. This computer program has been validated by five developers in a real case study. The results of the computer program agreed with the actual contractor selected by the developers of the project. The new contribution of this paper lies in the fact that it implements subjective judgment using fuzzy logic in the contractor selection decision and introduces multiple decision-makers into the quantitative solution introduced in the research reported in this paper.