Managing new product definition in highly dynamic environments
Management Science
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Product Development Decisions: A Review of the Literature
Management Science
Solving nonstationary infinite horizon stochastic production planning problems
Operations Research Letters
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Recent research suggests that new product specifications evolve during its realization. In this paper, we introduce a nonstationary Markovian model that supports the dynamic achievement of the new product definition without precedence constraints, taking into account both market and technological uncertainty. We use lattice programming techniques to prove the existence of a nondecreasing monotonic optimal policy. Thus, we enable a more efficient computation of optimal policies of the Markov decision process. We also prove that the monotonic optimal paths are robust to the variation of key-parameters as the solving rate of the design activities and the safety margin for achieving the new product at the deadline.