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

Abbas Toloie Eshlaghy and Farshad Faezy Razi

International Journal of Business Information Systems, 2015, vol. 18, issue 2, 141-159

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.

Keywords: grey relational analysis; GRA; k-means clustering; grey-based k-means; genetic algorithms; GAs; project selection; research and development; R%D projects; project management; project allocation. (search for similar items in EconPapers)
Date: 2015
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