1. IND E 410 (Linear and Network Programming): This is the first class in a three-class sequence in Operations Research for undergraduate students in engineering. It covers topics such as the simplex method; linear programming duality; sensitivity analysis; the dual simplex method; the transportation simplex method; and minimum cost network flow, maximum flow, minimum spanning tree, and shortest path problems.
2. IND E 411 (Stochastic Models and Decision Analysis): This is the second class in the undergraduate Operations Research sequence. It covers topics such as probabilistic decision trees; expected value of perfect information; discrete-time, finite-state Markov chains; continuous-time Markov chains; and queuing models.
3. IND E 412 (Integer, Dynamic and Non-linear Programming): This third class in the Operations Research sequence covers topics such as deterministic and stochastic dynamic programming; Lagrangian duality in integer programming; branch-and-bound and other methods for integer programming; gradient search and Newton's method for unconstrained, non-linear optimization; and Karush-Kuhn-Tucker conditions for constrained, non-linear optimization. If there is time, I sometimes also cover two-person zero sum games in this class.
The textbook for the above sequence is "Introduction to Operations Research" by Hillier and Lieberman.
1. IND E 513 (Linear Optimization in Engineering): This class covers convex sets and functions; polyhedral geometry; equivalence of extreme points and basic feasible solutions; simplex method; duality and Farkas Lemmas; interior point methods; and minimum cost network flow problems. The textbook for this class is "Introduction to Linear Optimization" by Bertsimas and Tsitsiklis.
2. IND E 508 (Stochastic Processes in Engineering): This class covers stochastic models without relying on measure theory. It includes topics such as Poisson processes; renewal processes; discrete-time and continuous-time Markov chains; and Martingales. The textbook is "Stochastic Processes" by Ross.