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Courses
- Optimization and Performance Analysis (60003) Course summary:
- Introduction to Probability (90911) Course summary:
Abstract:
The course focuses on formulating and solving optimization problems using mathematical models. During the course, students will study the following topics:
Linear Optimization: formulations, duality, complementary slackness.
Integer Linear Optimization: formulations, branch-and-bound method.
Dynamic Programming principles and examples.
Nonlinear Optimization: convex optimization, unconstrained optimization problems, first and second-order optimality conditions, gradient-based computational methods.
Constrained Optimization: KKT conditions, duality.
The course will include the use of Excel software for solving optimization problems.Abstract:
Basic concepts in probability theory: sample space, elementary theorems, combinatorial calculations, conditional probability and independence, random discrete variables, expected value and variance, special random variables,
multivariate variables, central limit theorem. Basic concepts in statistics: statistical estimation and testing, confidence intervals.