A new compromise solution method for fuzzy group decision-making problems with an application to the contractor selection

This paper presents a novel compromise solution method for solving fuzzy group decision-making problems by a group of experts, which can determine the best alternative by considering both conflicting quantitative and qualitative evaluation criteria in real-life applications. The compromise solution method is developed based on the concept that the chosen alternative should be as close as possible to the positive ideal solution and as far away from the negative ideal solution as possible concurrently. The performance rating values of alternatives versus conflicting criteria as well as the weights of criteria are described by linguistic variables with multi-judges and are converted to triangular fuzzy numbers. Then, a new collective index is introduced to distinguish among potential alternatives in the assessment process with respect to subjective judgment and objective information. Finally, a real case study and an application example for a contractor selection problem are provided in construction industry to demonstrate the implementation process of the proposed method.