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

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.