R&D pipeline management: Task interdependencies and risk management

Matthew Colvin, Christos T. Maravelias

Research output: Contribution to journalArticlepeer-review

48 Scopus citations


Maintaining a rich research and development (R&D) pipeline is the key to remaining competitive in many industrial sectors. Due to its nature, R&D activities are subject to multiple sources of uncertainty, the modeling of which is compounded by the ability of the decision maker to alter the underlying process. In this paper, we present a multi-stage stochastic programming framework for R&D pipeline management, which demonstrates how essential considerations can be modeled in an efficient manner including: (i) the selection and scheduling of R&D tasks with general precedence constraints under pass/fail uncertainty, and (ii) resource planning decisions (expansion/contraction and outsourcing) for multiple resource types. Furthermore, we study interdependencies between tasks in terms of probability of success, resource usage and market impact. Finally, we explore risk management approaches, including novel formulations for value at risk and conditional value at risk.

Original languageEnglish (US)
Pages (from-to)616-628
Number of pages13
JournalEuropean Journal of Operational Research
Issue number3
StatePublished - Dec 16 2011
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management


  • Project scheduling
  • Research and development pipeline
  • Resource planning
  • Stochastic programming


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