Project selection with outsourcing view using Fuzzy TOPSIS linear assignment programming

Nowadays most of organizations, especially in public sector, tend to outsource their projects. In these cases two major problems arise: project selection and contractor selection. There are many papers have argued separately about project selection and contractor selection in which often some evaluation criteria and a selection method are proposed independently. In this paper we propose a method for selecting projects and related contractors simultaneously in which firstly contractors that have not minimal qualifications are eliminated from consideration, then closeness coefficient of contractors to each proposal will be computed by Fuzzy TOPSIS method and finally these coefficients as a successful indicators for each contractor will be fed in to a linear programming to select most profitable projects and related contractors with respect to the constraints. In this paper we propose a method for selecting projects and related contractors simultaneously. The proposed approach contains 3 Phases including prequalification (Phase1), computing closeness coefficient (CC) for each project-contractor by using fuzzy TOPSIS method (Phase2) and selecting projects and assigning each project to most qualified contractor by solving a Linear Programming with respect to economic characteristics of each project, closeness coefficient of each contractor to projects and some constraints such as budget available and strategic limitations (Phase3). Also a numerical example will be illustrated to show the application of the proposed method.