A hybrid grey-based k-means and genetic algorithm for project selection
by Abbas Toloie Eshlaghy; Farshad Faezy Razi
International Journal of Business Information Systems (IJBIS), Vol. 18, No. 2, 2015

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.

Online publication date: Sat, 28-Mar-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Information Systems (IJBIS):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com