Level:
Graduate
Instructors:
Prof. Robert Freund
Prof. Jie Sun
Prof. Thomas Magnanti
An image of transportation demand and computational solutions. (Image courtesy of Andreas Schulz.)
Course Features
Course Highlights
This course features a comprehensive set of
lecture notes,
covering topics from basic principles such as Linear Optimization to
sophisticated real-world applications. Also, there is a complete
set of problem sets in the
assignments section.
Course Description
This class is an applications-oriented course covering the modeling of
large-scale systems in decision-making domains and the optimization of
such systems using state-of-the-art optimization tools. Application
domains include: transportation and logistics planning, pattern
classification and image processing, data mining, design of structures,
scheduling in large systems, supply-chain management, financial
engineering, and telecommunications systems planning. Modeling tools
and techniques include linear, network, discrete and nonlinear
optimization, heuristic methods, sensitivity and post-optimality
analysis, decomposition methods for large-scale systems, and stochastic
optimization.
This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5223 (System Optimisation: Models and Computation).