A NEW FUZZY APPROACH FOR PROJECT SELECTION WITH OUTSOURCING VIEWPOINT

Nowadays most of the organizations tend to outsource their projects. In these cases, two major problems arise: project selection and contractor selection. There are many papers which have argued separately about project and contractor selections. In this paper, we propose a decision support system for selecting projects and related contractors. The proposed approach contains three phases including contractors' prequalification (Phase 1), computing success coefficient of each contractor in projects using fuzzy TOPSIS method (Phase 2), and selecting projects and assigning each project to the most appropriate contractor using a linear programming model (Phase 3). Finally, a numerical example is illustrated to show the application of the proposed method.