A model for ITIS project portfolio selection in the presence of uncertainty Combination of fuzzy multi-criteria decision making and fuzzy mathematical programming
Creators: name: Seifbarghy, Mehdi
name: Reihaneh Amel Sadeghi
Publisher: name: figshare
Year: 2020
Subjects: subject: 99902 Engineering Instrumentation
subject: FOS: Other engineering and technologies
subject: FOS: Other engineering and technologies
subject: 90603 Industrial Electronics
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: 90505 Infrastructure Engineering and Asset Management
subject: FOS: Civil engineering
subject: FOS: Civil engineering
subject: 91599 Interdisciplinary Engineering not elsewhere classified
subject: 91003 Machine Tools
subject: 91004 Machining
subject: 91099 Manufacturing Engineering not elsewhere classified
subject: 91005 Manufacturing Management
subject: 91006 Manufacturing Processes and Technologies (excl. Textiles)
subject: 91007 Manufacturing Robotics and Mechatronics (excl. Automotive Mechatronics)
subject: 91008 Manufacturing Safety and Quality
subject: 91199 Maritime Engineering not elsewhere classified
subject: FOS: Environmental engineering
subject: FOS: Environmental engineering
subject: 91299 Materials Engineering not elsewhere classified
subject: FOS: Materials engineering
subject: FOS: Materials engineering
subject: Mechanical Engineering
subject: FOS: Mechanical engineering
subject: FOS: Mechanical engineering
subject: 91399 Mechanical Engineering not elsewhere classified
subject: 90304 Medical Devices
subject: FOS: Medical engineering
subject: FOS: Medical engineering
subject: 90404 Membrane and Separation Technologies
subject: FOS: Chemical engineering
subject: FOS: Chemical engineering
subject: 91207 Metals and Alloy Materials
subject: 91306 Microelectromechanical Systems (MEMS)
subject: 90604 Microelectronics and Integrated Circuits
subject: 91009 Microtechnology
subject: 91404 Mineral Processing/Beneficiation
subject: 91405 Mining Engineering
subject: 91102 Naval Architecture
subject: 90904 Navigation and Position Fixing
subject: 90405 Non-automotive Combustion and Fuel Engineering (incl. Alternative/Renewable Fuels)

description: IT/IS represents a substantial financial investment for many organizations. Making IT project portfolio decision is difficult, because long lead times of IT project and market and technology dynamics lead to unavailable and unreliable collected data for portfolio management. This uncertainty has been modeled using fuzzy concepts. We need a collective model that will help decision-makers evaluate potential new investment projects in an easy, cost-effective, and collective manner. Hence, we propose a new approach based on the fuzzy multi-criteria decision model (FMCDM) and a fuzzy binary multi-objective linear programming model, featuring a 2-stage evaluation and selection process with 19 criteria for IT/IS investment. At the first stage, evaluation, all stakeholders in a corporation can decide the relative weights they give to the criteria when they evaluate a new IT/IS project by using linguistic values. Experts can also use linguistic values to evaluate all candidates easily. Only an Excel worksheet is needed to obtain an evaluation result. The results of FMCDM of the aforementioned are treated as input of a fuzzy binary mathematical programming model as coefficients of objective functions, which is the second stage of the proposed model. In the second stage, selection, we have developed a fuzzy binary mathematical programming model in order to find an optimum combination of investment portfolio considering a multi-objective measurement function in three ways: to maximize the benefit, to maximize the confidence level and to minimize the cost of projects in a complete ambiguous condition, when their initial investment costs, profits, confidence levels, resource requirements and total available budgets are assumed to be uncertain. We solve it in Lingo 10.0 through a Branch and Bound algorithm. In this paper, for the first time we have developed a model for IT/IS project portfolio selection in presence of uncertainty that is combination of fuzzy multi-criteria decision making and fuzzy mathematical programming with 19 criteria that is compatible with the nature of IT projects. We conduct a case study to show how this model can be used and discuss the results.