MA381 Course Description

This course provides an undergraduate presentation of nonlinear topics in mathematical programming that builds on multivariable Calculus II. The emphasis of this course is on developing a conceptual understanding of the fundamental topics introduced. These topics include general convexity, convex functions, derivative-based multivariable search techniques, minima and maxima of convex functions, gradients, hessian matrices, Lagrange Multipliers, and Kuhn-Tucker optimality conditions, and constrained and unconstrained optimization. Computer software is used to explore and expose various key ideas throughout the course. We will use the computer programming language Python to explore and expose various key ideas daily.

Assigned reading and homework below reference each of the three course textbooks with the following convention:

• F: Fox, William P. Nonlinear Optimization – Models and Application. 2021

• S: Stewart, James. Calculus: Early Transcendentals, Revised 7^th, or 8^th Edition.

• Cocalc – you will need a cocalc account as soon as possible. https://cocalc.com/

Module Folder: https://www.youtube.com/watch?v=-rZEuSPUW40