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A hybrid grey-based k-means and genetic algorithm for project selection

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  • Abbas Toloie Eshlaghy
  • Farshad Faezy Razi

Abstract

Research and development (R%D) project selection is an important function for organisations with R%D project management. Project portfolio managers are preferred a portfolio of projects with multiple attribute criteria. So, project portfolio selection problem is a decision making process. This paper presents an integrated framework for project selection and project management approach using grey-based k-means and genetic algorithms. The proposed approach of this paper first cluster different projects based on k-means algorithm and then ranks R%D projects by grey relational analysis (GRA) model. In this paper, project allocation is selected by genetic algorithm (GA). The proposed framework is tested in a case study to show its usefulness and applicability in practice.

Suggested Citation

  • Abbas Toloie Eshlaghy & Farshad Faezy Razi, 2015. "A hybrid grey-based k-means and genetic algorithm for project selection," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 18(2), pages 141-159.
    • Handle: RePEc:ids:ijbisy:v:18:y:2015:i:2:p:141-159
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    Cited by:

    1. Dalton Garcia Borges de Souza & Erivelton Antonio dos Santos & Nei Yoshihiro Soma & Carlos Eduardo Sanches da Silva, 2021. "MCDM-Based R&D Project Selection: A Systematic Literature Review," Sustainability, MDPI, vol. 13(21), pages 1-34, October.

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