Convex Optimization
This course is about optimizing systems of engineering and economic interest using linear and nonlinear programming. The focus is on convex optimization problems, which have only one best cost, design, size etc. We consider problems such as least squares regression, supply chain management, batch process networks, continuous flow networks, portfolio optimization, and other examples across all engineering disciplines. Students learn most about optimization theory and problem formulation, with some computational component. By the end of the course, students should be able to: create optimization problems from a physical situation, identify whether a problem can be solved or not, transform problems into equivalent forms, list optimality conditions for problems, find the dual of a problem and identify its relation to the primal, and use numerical algorithms to solve convex programming problems using a computer.
Same as EID 488
Prerequisite or Corequisite: ChE 352 or ME/ESC 251 or Ma 326 or Ma 352
Credits: 3.00
Course Code: ChE 488
