Spring 2020 - MATH 308 D100
Linear Optimization (3)
Class Number: 3746
Delivery Method: In Person
Course Times + Location:
Mo, We, Fr 2:30 PM – 3:20 PM
AQ 3154, Burnaby
Exam Times + Location:
Apr 23, 2020
12:00 PM – 3:00 PM
SSCB 9200, Burnaby
1 778 782-4699
Prerequisites:MATH 150, 151, 154, or 157 and MATH 240 or 232.
Linear programming modelling. The simplex method and its variants. Duality theory. Post-optimality analysis. Applications and software. Additional topics may include: game theory, network simplex algorithm, and convex sets. Quantitative.
Couse topics: Theory and applications of linear programming, geometric and computational considerations, networks, applications of duality.
Outline:1. Linear Programming.
Examples - formulation of optimization problems as linear programming problems. Canonical forms for linear programming problems. Polyhedral convex sets.
2. The Simplex Algorithm.
Tucker Tableaus. The simplex algorithm for maximum tableaus and minimum tableaus. Cycling.
3. Noncanonical Linear Programming Problems.
Unconstrained variables. Equations as constraints.
4. Duality Theory
The dual simplex algorithm. Complementary slackness. The duality theorem.
5. Application: Matrix Games.Linear Programming formulation of matrix games. The von Neumann minimax theorem.
6. Other applications (as time permits).
- Homework (6 Assignments, Equally Weighted) 15%
- Midterm 1 (Early February) 15%
- Midterm 2 (Mid March) 20%
- Final Exam 50%
THE INSTRUCTOR RESERVES THE RIGHT TO CHANGE ANY OF THE ABOVE INFORMATION.
Students should be aware that they have certain rights to confidentiality concerning the return of course papers and the posting of marks.
Please pay careful attention to the options discussed in class at the beginning of the semesters.
Some Maple worksheets will be posted on Canvas
Linear Programming and Its Applications
Strayer, James K.
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