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A hybrid mathematical programming model for optimal project portfolio selection using fuzzy inference system and

Madjid Tavana1, Ghasem Khosrojerdi2, Hassan Mina3

  • 1Business Systems and Analytics Department, Distinguished Chair of Business Analytics, La Salle University, Philadelphia, PA 19141, USA; Business Information Systems Department, Faculty of Business Administration and Economics, University of Paderborn, D-33098 Paderborn, Germany.

Evaluation and Program Planning
|August 24, 2019
PubMed
Summary

Selecting optimal Information Technology (IT) projects is complex. This study introduces a two-stage hybrid model integrating Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Inference System (FIS) to maximize business value while minimizing risks.

Keywords:
Analytic hierarchy processFuzzy inference systemMathematical programmingProject portfolio selection

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Area of Science:

  • Operations Research
  • Information Technology Management
  • Decision Science

Background:

  • Project portfolio management (PPM) aims to maximize business value through optimal project selection.
  • Selecting Information Technology (IT) projects is challenging due to inherent complexities, uncertainties, and mixed quantitative/qualitative criteria.
  • Existing methods often struggle to balance strategic goals with operational realities and risk assessment.

Purpose of the Study:

  • To develop a robust framework for optimal IT project portfolio selection.
  • To integrate quantitative and qualitative factors for a comprehensive evaluation.
  • To maximize project benefits while simultaneously minimizing associated risks.

Main Methods:

  • A two-stage hybrid mathematical programming model was constructed.
  • Integration of Fuzzy Analytic Hierarchy Process (FAHP) for criteria weighting.
  • Incorporation of Fuzzy Inference System (FIS) for risk and benefit assessment.
  • Consideration of budget constraints within the model.

Main Results:

  • The proposed hybrid model effectively handles both quantitative and qualitative decision criteria.
  • The two-stage approach successfully balances maximizing project benefits and minimizing risks.
  • A real-world case study in the cybersecurity industry demonstrated the method's applicability and efficacy.

Conclusions:

  • The FAHP-FIS hybrid model offers a superior approach to IT project portfolio selection.
  • This framework enhances decision-making by systematically incorporating diverse criteria and risks.
  • The method provides a practical tool for organizations seeking to optimize their IT investments.