ISyE 6669: Deterministic Optimization

Fall 2002


UPDATES:

INSTRUCTOR:
Shabbir Ahmed
Office:     Rm 325 Groseclose Bld.
E-mail:     sahmed@isye.gatech.edu
Phone:    404-894-2320
Fax:         404-894-2301
Office hours: Wednesdays 2:00-4:00pm  (or by appointment).

Note: Visit the class website (http://www.isye.gatech.edu/~sahmed/isye6669) regularly for notices and updates.

TEACHING ASSISTANT:
Cheng-Huang "Alexander" Hung
E-mail:    ehung@isye.isye.gatech.edu
Office:                Rm. 304 Groseclose (ISyE Bld)
Office hours:     2:30-4:00pm Tu-Th.
CLASS MEETINGS:
W200 Van Leer-Elec Eng., MWF 1:05-1:55pm.
PRE-REQUISITES: TEXTBOOK:
Ronald L. Rardin, "Optimization in Operations Research," Prentice Hall, NJ, 1998.
Note: This course will also cover some material not in the textbook, and not all material in the book will be covered in the course.
GRADING:
  • 10% Homework
  • 70% Exams
  • 20% Course Project
    • HOMEWORK AND PROJECTS:
    Homeworks are meant as individual assignments. Although you are encouraged to consult with your class-mates, each student should submit his/her own work. Homework assignments will be based on theoretical concepts covered in class as well as small computational exercises. You are encouraged to start on these assignments as early as possible so as to be able to complete them by the due date. Late homework submissions will not be accepted, unless due to serious unavoidable circumstances.

    The course project will be due at the end of the semester. The projects will require you develop, analyze and implement an optimization model from a real life application, and develop data processing routines, optimization algorithms, as well as solution validation routines. Projects are intended for groups of up to four students. Further details will be provided within the first few weeks of class. You are encouraged to start early to be able to do a good job on the project.

    EXAMS:
    There will be two in-class midterm exams, plus a cumulative final exam.  The exact dates of the midterms will depend on the pace of the course, and will be announced later.  The final exam will be given according to the Georgia Tech finals-week schedule.  Exams may contain a take-home component.
    ACADEMIC HONOR CODE:
    All course participants (myself, teaching assistants, and students) are expected and required to abide by the letter and the spirit of the Georgia Tech honor code.  If there is any way in which I can help you in complying with the honor code, please do not hesitate to ask.
    TENTATIVE COURSE TOPICS:
     
    TOPIC
    SAMPLE CONTENTS
    BOOKS SECTIONS
    Introduction Modeling real life applications (*), types of optimization models (*) etc. 1.1-1.4; 2.1-2.5
    Optimization fundamentals Properties of sets and functions, convexity, well-defined problems.  
    Unconstrained optimization Classical calculus based optimization (*), Golden section, Newton's method etc. 13.1-13.8
    Linear Programming Modeling (*), geometry (*), the Simplex method (*), duality and sensitivity, interior point methods, large-scale LP algorithms. 4.1-4.6; 5.1-5.3; 5.8; 7.1-7.7
    Constrained Non-linear Programming Models, KKT optimality conditions. 14.1-14.4
    Quadratic Programming Models, algorithms, SQP methods 14.2
    Integer Programming Modeling (*), LP relaxation, Branch & bound (*), cutting planes, heuristics 11.1-11.7; 12.1-12.8
    Network Flows Terminology (*), total unimodularity, shortest path problems, min-cost flow problems 10.1,10.4-10.6, 9.1,9.5.
      (*) Students are expected to have some familiarity with these topics from pre-requisite courses.
    Note: The above is only a tentative list. There may be additions and/or deletions to the course content based upon the pace of the class.

    © Shabbir Ahmed (sahmed@isye.gatech.edu)