Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering.

Formulate linear and integer programming problems for solving commonly encountered optimization problems. Understand how approximation algorithms compute solutions that are guaranteed to be within ...

We develop a modular and tractable framework for solving an adaptive distributionally robust linear optimization problem, where we minimize the worst-case expected cost over an ambiguity set of ...

Course Description This course discusses basic convex analysis (convex sets, functions, and optimization problems), optimization theory (linear, quadratic, semidefinite, and geometric programming; ...

Multiplayer algorithms (particle swarm, leapfrogging, differential evolution) broadly explore the surface, increasing the probability that the global will be discovered. Interior/exterior point: ...

Using a range of real datasets and basic Python libraries for data manipulation, vector/matrix algebra, and automatic differentiation students will code up - from scratch - fundamental optimization ...

Thanks to these abilities, they can already topple complex linear differential equations exponentially faster than classical machines. Researchers have long hoped they could similarly tame nonlinear ...