Implementing TOPSIS Method for Project Selection Under Fuzzy Environment

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 assignment programming to select most profitable projects and related contractors with respect to the constraints. The proposed approach contains ٣ Phases including prequalification ( Phase١), computing closeness coefficient ( CC) for each project- contractor using fuzzy TOPSIS method ( Phase٢) and selecting projects and assigning each project to most appropriate contractor using Linear Assignment 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 ( Phase٣). At the end of this paper a numerical example will be illustrated to show the application of the proposed method.

Keywords:

project selection , contractor selection , Fuzzy TOPSIS , Integer Programming