Continuous Optimization

Undergraduate

Problems and methods in non-linear optimization. Classical optimization in Rn: inequality constraints, Lagrangian, duality, convexity. Non-linear programming. Search methods for unconstrained optimization. Gradient methods for unconstrained optimization. Constrained optimization. Dynamic programming. Course Format: Lectures, 3 hours per week; lab/tutorial, 1 hour per week. Prerequisite(s): MATH 2P03 or permission of the instructor Course Notes: This course may be offered in multiple modes of delivery. The method of delivery will be listed on the academic timetable, in the applicable term.