Fuzzy MATLAB Approach to Construction Contractor Selection

Contractor selection is the process of selecting the most appropriate contractor to deliver the project as specified. Construction clients are becoming more aware of the fact that selection of a contractor based on tender price alone is quite risky and may lead to the failure of the project in terms of time delay and poor quality standards. Contractor prequalification involves the screening of contractors by a project owner, according to a given set of criteria, in order to determine their competence to perform the work, if awarded. This study presents an approach to prioritize competitive contractors at the pre bidding stage for construction projects by utilizing fuzzy inference system. Initially, the main quantitative and qualitative criteria affecting the contractor selection process are identified and studied. The effective criteria in the selection process were obtained from experts and literatures. A structured questionnaire was designed and sent to experts in construction projects in Kerala. The fuzzy weightage was used to prioritize these criteria and a case study for the construction of an apartment was conducted to illustrate the most important criteria obtained from the questionnaire. Subsequently, fuzzy mat lab was utilized to develop the selection model.The applicability of the proposed model was tested using a real case of apartment construction projects. It was concluded that using the lowest bid price as a sole criterion for selecting the best contractors may not result in an optimum solution. One major advantage of the proposed method is that it makes the selection process more systematic and realistic as the use of fuzzy set theory allows the decision maker to express their assessment on contractors? performance in linguistic terms rather than a crisp value.