Class time: Monday, Wednesday, and Friday 3:00 - 4:00 pm
               Class Room: 228 NSC


  Instructors:
               Dr. Kurt Hacker
               Office: 805 Furnas Hall and 5 Norton Hall
               E-mail: khacker@eng.buffalo.edu
               Office Hrs: 11-12 Tuesday or by appointment

               John Eddy
               Office: 805 Furnas Hall
               Phone: 645-2593 Ext. 2261
               E-mail: johneddy@eng.buffalo.edu

  TA:
               Mr. Tung King See
               Office: 805 Furnas Hall
               E-mail: tungsee@eng.buffalo.edu
               Office Hrs: 1:30-2:30 Tuesday and Thursday

Course text: None Required- Suggested Text: "How to Solve It: Modern Heuristics" by Michalewicz and Fogel. Available on Amazon.com

Description:

Optimization involves finding the "best" solution according to specified criteria. In Engineering Design, this might typically be minimum cost or weight, maximum quality or efficiency, or some other performance index pertaining to a disciplinary objective. Realistic optimal design involves not only an objective function to be minimized or maximized, but also constraints that represent limitations on the mathematical design space. Numerical program ming requires the mathematical representation of the design space in terms of "design variables", which are parameters that signify some potential for change. Generally, the problems of interest in engineering are of a nonlinear nature; the dependence of the objective function and constraints on the design variables is not linear. Engineering Optimization I (MAE 550) introduces the traditional nonlinear optimization methods that can be used to solve a wide variety of design problems across all engineeri ng disciplines. This course will address newer topics not covered in MAE 550; many such techniques are less based on gradient-based calculus, and based more on rigorous experience and successful usage. "Heuristics", if you will.

Subject Matter

Lectures

Lecturer

Homework

Introduction, Optimization overview

3

Hacker

 

Enumerative Search and Related Topics

2

Hacker

HW 1

Clustering Methods

2

Hacker

 

Simulated Annealing

3

Hacker

HW 2

Quiz #1

 

 

 

Genetic Algorithms/Evolutionary Optimization

6

Eddy

HW 3

Taguchiís Method

4

Eddy

 

Quiz #2

 

 

 

Branch and Bound

4

Hacker

HW 4

Tabu Search

3

Hacker

HW 5

Hybrid Methods

1

Hacker

 

Quiz #3

 

 

 

Neural Networks

2

Eddy

HW 6

Fuzzy Logic

2

Eddy

 

Multiobjective Optimization

2

Eddy

 

Special Topics

2

Eddy

 

Quiz #4

 

 

 

General comments:
  • Being punctual is part of being professional. Please be on-time for lecture.
  • Being prepared is part of being professional. Please spend 5-10 minutes prior to each lecture reviewing your notes from the previous lecture.
  • Homework deadlines are very important in this class. Please hand in your homework assignments on time.
  • There is no final exam for this class. However, project presentations will be held during our scheduled final exam period. All students of this class are required to attend the project presentations.
  • Academic Dishonesty (cheating, plagiarism, etc.) of any kind is immediate grounds for receiving an F in this course.

Matlab:

Use of the computer program MATLAB may be helpful in the completion of your homework assignments and projects. It is available on the engineering network. Check out the tutorial at http://www.engin.umich.edu/group/ctm/.

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