Project Scope Partitioning by Clustering Features into Releases of Long R&D Projects

R&D projects are characterized by a long planning horizon, which entails the policy of release management. The intermediate releases enable the organization to maximize the value for a given investment. Myopic version of this problem is known as the Next Release Problem (NRP). A central issue ad...

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Bibliographic Details
Published in:Procedia computer science 2016, Vol.100, p.1235-1241
Main Authors: Etgar, Ran, Gelbard, Roy, Cohen, Yuval
Format: Article
Language:English
Subjects:
releases
Scheuling
Scope of work
version
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Summary:R&D projects are characterized by a long planning horizon, which entails the policy of release management. The intermediate releases enable the organization to maximize the value for a given investment. Myopic version of this problem is known as the Next Release Problem (NRP). A central issue addressed by these projects is determining which features should be included in the next release. The choice of features impacts the value of the release, but also impacts the required workload, and future development of other features. NRP can be expanded to include the later releases. This problem is NP-hard and thus cannot be solved analytically. In this work we apply a simple clustering algorithm, based on novel similarity coefficients to reduce complexity. Our goal is to provide a near-optimal yet simple method for quantitatively determining the feature content of all project releases.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2016.09.154