Chapter 4: Readings

Many of the topics are organized around sequential decision problems presented in

Warren Powell, Sequential Decision Analytics and Modeling, NOW Press, 2022 (available for free download from https://tinyurl.com/sdamodeling). Below I refer to this as “SDAM.”

Readings from SDAM are indicated at the beginning of each topic (or subtopic).

Occasionally I refer to material in my graduate-level book:

Warren Powell, Reinforcement Learning and Stochastic Optimization, Wiley, 2022 (see https://tinyurl.com/RLandSO/ for an overview). Below I refer to this as “RLSO.”

RLSO is not appropriate for an introductory course such as this, but I recommend that the instructor have a copy of the book.

There are blocks of material on mature topics like linear, integer, and nonlinear programming. I assume that any professor teaching a course in optimization will already have a favorite book they like to use for these topics. We encourage, for an introductory course like this, putting more emphasis on describing what these problems are and how they are used, with less emphasis on algorithms, especially when these are widely available in packages.