Math 417 / 487 - Fall 2011
We will give a thorough introduction to the main areas of mathematical programming. We start by studying linear programming (LP) including modelling, the Simplex Algorithm, sensitivity analysis, parametric programming and economic applications. We also discuss briefly polynomial-time algorithms for linear programming such as the ellipsoid method and interior point methods. We give an overview of convex analysis to support our handling of integer programming, including cutting plane theory. We also study topics in nonlinear programming including optimality conditions, convex programming and an introduction to geometric programming. We plan to also give an introduction to optimization under uncertainty, including robust optimization and stochastic programming.
Students should know the basics from Calculus and Linear Algebra.
NOTE: Math 417/487 may be used as a pre-requisite for Discrete Optimization II
- Yori Zwols
- Office: Burnside 1243
- Office hours: Thursdays 3pm-5pm
- Email: yori dot zwols at mcgill dot ca
- Time: Wednesday and Friday 10:05 AM - 11:25 AM.
- Location: Burnside Hall 1B23
The main course text is: Applied Mathematical Programming by Bradley, Hax, and Magnanti (Addison-Wesley, 1977)
This covers almost all of our material on LP and Integer Programming. Extra material will be assigned when we discuss other topics such as stochastic programming, geometric programming etc.
- Course Notes (I will try to post updated notes after every lecture)
Course grades will be based upon assignments (20%), midterm (30%) and a final exam (50%).
Assignment #1 (due Wednesday September 14th at the beginning of class)
- Math 417: Exercises 1, 5, 6, 25, 28 from the textbook; Exercises 1, 2 from the notes.
- Math 487/Mining students: Exercises 1, 5, 6, 7, 25, 26, 28 from the textbook; Exercises 1, 2 from the notes.