A fuzzy MODM approach for project selection models With fuzzy constraints

Project selection problems are classified to some taxonomies. The first taxonomy arises in the context of research and development, information technology, and capital budgeting. The second one classifies project selection models into the management science stream and the financial optimization stream. We focus on the first taxonomy. Thus in this paper a comprehensive multi-objective mathematical model is proposed which is a combination of the information system (IS), research and development (R&D) and capital budgeting project selection problems. There are some uncertain elements could affect on project evaluation if we assume them as crisp parameters. To make a decision with considering real conditions and due to inherent uncertainty in project team costs, risk factors, cost of the over-allocated project managers, project completion times, and cost of the under-allocated professional manpower and so on, they are treated as fuzzy input data. Also in order to take advantage of soft computing, some constraints and objective functions which have uncertainty in their definitions are considered as vague elements. Inserting these two types of imprecision into the model, results in multi-objective fuzzy model. The flexible (fuzzy) programming is applied to cover vague elements and the possibilistic programming is implemented to face against the inherent fuzzy parameters. Applying these approaches simultaneously are converted the model into an equivalent multi-objective crisp model. At last to achieve the final auxiliary single-objective crisp formulation, a fuzzy multiobjective decision making (FMODM) approach is implemented. To illustrate the validity of the model, a numerical example is solved and the obtained results are reported