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Course number and title: EE236A Linear Programming
Credits: 4
Instructor(s)-in-charge: F. Vatan (farrokh.vatan@jpl.nasa.gov)
Course type: Lecture
Required or Elective: A Signals and Systems course.
Course Schedule:
Lecture: 4 hrs/week.
Outside Study: 8 hrs/week.
Office Hours: 2 hrs/week.
 
Course Assessment:
Homework: About 8 homework assignments.
Exams: 1 final exam.
 
Grading Policy: Typically, 30% homework assignments, 70% final.
Course Prerequisites: MATH 115A or equivalent knowledge of linear algebra.
Catalog Description: Basic graduate course in linear optimization. Geometry of linear programming. Duality. Simplex method. Interior-point methods. Decomposition and large-scale linear programming. Quadratic programming and complementary pivot theory. Engineering applications. Introduction to integer linear programming and computational complexity theory.  
Textbook and any related course material:
Instructor's notes and other course material available at www.ee.ucla.edu/ee236a.
 
Course Website
Additional Course Website
Topics covered in the course:
Definitions and geometry of linear programming.
Applications of linear programming.
Duality.
The simplex method.
Interior-point methods.
Introduction to one or more of the following topics: linear network flow optimization, large-scale linear programming, integer linear programming.
Will this course involve computer assignments? NO Will this course have TA(s) when it is offered? NO

:: Last modified: November 2011 by J. Wan ::

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