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- W2065657859 abstract "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." @default.
- W2065657859 created "2016-06-24" @default.
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- W2065657859 date "2011-12-01" @default.
- W2065657859 modified "2023-09-29" @default.
- W2065657859 title "R&D pipeline management: Task interdependencies and risk management" @default.
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- W2065657859 doi "https://doi.org/10.1016/j.ejor.2011.06.023" @default.
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