IND E 325
Nonlinear optimization and stochastic systems analysis to industrial engineering problems. Topics include: nonlinear programming, dynamic programming, Markov chains, queuing theory, and queuing applications. Prerequisite: IND E 315; IND E 324. Offered: W.
The class covers topics in stochastic models, nonlinear programming and dynamic programming. In particular, we will look at Markov processes and chains, queueing theory and applications, fundamental aspects of nonlinear programming, and dynamic programming modeling and applications.
The class will meet twice weekly. The regular meeting times will mainly be dedicated to lectures, but will also include some Q&A and review sessions.
The class will assume fundamental knowledge of probability theory and statistics. Some review of IndE 324 material is encouraged.
Class Assignments and Grading
Assignments will be analysis- and application-oriented, and each will include 2-3 cases/questions. Teams of two will be accepted. The assignments will be due within a week after handed. No late submission will be accepted except in cases of verifiable emergencies.
Midterm and final exams will be open book and notes, and focus towards theoretical aspects but will also test problem-solving skills. Exam dates are fixed.
Assignment 1, worth 10% Assignment 2, worth 15% Assignment 3, worth 10% Assignment 4, worth 15% Midterm, worth 20% Final exam, worth 30%