FUZZY MATHEMATICAL PLANNING MODEL FOR PROJECT PORTFOLIO SELECTION CONSIDERING PROJECT INTERDEPENDENCIES
Projects are used in most organizational structures including strong matrix, weak matrix, balance matrix, project-oriented, virtual, hybrid, and project management oce to achieve the goals of the organization. Many organizations consider their successful projects as a competitive advantage and use a comprehensive portfolio management system to manage projects, plans, and operations to achieve their organizational goals. As project management has become more professional, the focus of organizations has shifted from management to one or more complex projects separately and to the management of an interconnected set of projects. Therefore, a formal portfolio management process is a requirement for integrated implementation and the use of a portfolio system to manage projects to achieve the goals and strategies of the organization based on the desired criteria of management, is necessary. Income sources in almost all of the project-based companies, especially in IT Industry, are highly dependent on the company's project revenue, so Project Portfolio Selection has always been one of their managers' main concerns. To maximize their business value and protability, these companies dene appropriate projects in specic time horizons. Because the projects compete for resources, the interdependence between an organization's projects and their potential and actual impact on the portfolio selection has become particularly important to managers. Applying Analytical Hierarchy Process (AHP) technique and the Fuzzy Inference System (FIS), this paper presents a hybrid model of Fuzzy Mathematical Programming that seeks to select projects in a portfolio by creating maximum synergies between them in the presence of uncertainty. In the proposed model, the concept of synergy is used in such a way that time constraints, costs, and interactions between them are satised, and decision-makers have the opportunity to evaluate dierent selection modes. We used the fuzzy conditional programming approach in the objective function and the Jimenez method in constraints to defuzzify the problem. In order to express the eectiveness of the proposed model, it is applied in the telecom industry as a case study.
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