The Elements of Joint Learning and Optimization in Operations Management

<p>Part 1:&nbsp;Generic Tools.-&nbsp;Chapter 1:&nbsp;The Stochastic Multi-armed Bandit Problem.- Chapter 2:&nbsp;Reinforcement Learning.- Chapter 3:&nbsp;Optimal Learning and Optimal Design.-&nbsp;Part 2:&nbsp;Price Optimization.-&nbsp;Chapter 4:&nbsp;Dynamic Pricing with Demand Learning: Emerging Topics and State of the Art.- Chapter 5:&nbsp;Learning and Pricing with Inventory Constraints.- Chapter 6:&nbsp;Dynamic Pricing and Demand Learning in Nonstationary Environments.- Chapter 7:&nbsp;Pricing with High-Dimensional Data.-&nbsp;Part 3: Assortment Optimization.-&nbsp;Chapter 8:&nbsp;Nonparametric Estimation of Choice Models.- Chapter 9:&nbsp;The MNL-Bandit Problem.- Chapter 10:&nbsp;Dynamic Assortment Optimization: Beyond MNL Model.-&nbsp;Part 4:&nbsp;Inventory Optimization.-&nbsp;Chapter 11:&nbsp;Inventory Control with Censored Demand.- Chapter 12:&nbsp;Joint Pricing and Inventory Control with Demand Learning.- Chapter 13:&nbsp;Optimization in the Small-Data, Large-Scale Regime.-&nbsp;Part 5:&nbsp;Healthcare Operations.-&nbsp;Chapter 14:&nbsp;Bandit Procedures for Designing Patient-Centric Clinical Trials.- Chapter 15:&nbsp;Dynamic Treatment Regimes.</p>