Purdue University Graduate School
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Dissertation_LeiLi

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thesis
posted on 2023-07-26, 17:11 authored by Lei LiLei Li

In the real world, uncertainty is a common challenging problem faced by individuals, organizations, and firms. Decision quality is highly impacted by uncertainty because decision makers lack complete information and have to leverage the loss and gain in many possible outcomes or scenarios. This study explores dynamic decision making (with known distributions) and decision learning (with unknown distributions but some samples) in not-for-profit operations and supply chain management. We first study dynamic staffing for paid workers and volunteers with uncertain supply in a nonprofit operation where the optimal policy is too complex to compute and implement. Then, we consider dynamic inventory control and pricing under both supply and demand uncertainties where unmet demand is lost leading to a challenging non-concave dynamic problem. Furthermore, we explore decision learning from limited data of focal system and available data of related but different systems by transfer learning, cross learning, and co-learning utilizing the similarities among related systems.

History

Degree Type

  • Doctor of Philosophy

Department

  • Management

Campus location

  • West Lafayette

Advisor/Supervisor/Committee Chair

Qi Feng

Additional Committee Member 2

Gökçe Esenduran

Additional Committee Member 3

William Benjamin Haskell

Additional Committee Member 4

J. George Shanthikumar