Department of Electrical and
Computer Engineering
EEC 693 /
793
Special Topics: Genetic
Algorithms
Summer
2004
Description: Computer-based simulations of GAs (genetic algorithms) for optimization and engineering problems. After taking this course, the student should be able to implement a GA in Matlab (or some other high level programming language), be aware of the current state of the art in the field, and be able to conduct independent research in the field.
Text: David Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989
References: R. Haupt and S. Haupt, Practical Genetic Algorithms, John Wiley
& Sons, 1998
M. Mitchell, An
Introduction to Genetic Algorithms, The MIT Press, 1996
C. Reeves and J.
Rowe, Genetic Algorithms -
Principles and Perspectives, Kluwer Academic Publishers, 2003
M.
Jamshidi, Robust Control Systems with
Genetic Algorithms, CRC Press, 2003
D. Fogel, Evolutionary Computation: The Fossil
Record, IEEE Press, 1998
J. Koza, Genetic Programming, The MIT Press,
1992
D. Coley, An Introduction to
Genetic Algorithms for Scientists and Engineers, World Scientific,
1999
Z. Michalewicz, Genetic
Algorithms + Data Structures = Evolution Programs, Springer, 1996
L.
Davis, Handbook of Genetic
Algorithms, Van Nostrand Reinhold, 1991
J. Zurada, R. Marks, C. Robinson,
Computational Intelligence Imitating
Life, IEEE Press, 1994
M. Gen and R. Cheng, Genetic Algorithms and Engineering
Design, John Wiley & Sons, 1997
M. Gen and R. Cheng, Genetic Algorithms and Engineering
Optimization, John Wiley & Sons, 2000
A. Zalzala and P. Fleming, Genetic Algorithms in Engineering
Systems, The Institution of Electrical Engineers, 1997
J. Holland, Adaptation in Natural and Artificial
Systems, The MIT Press, 1992
Journals:
IEEE
Transactions on Evolutionary Computation
Machine Learning
Complex Systems
Complexity International
Evolutionary
Computation
Genetic Programming and
Evolvable Machines
A search for “genetic algorithms” on the
Internet leads to a lot of good web sites -
for example,
http://www.genetic-programming.org/
-
John Koza’s web site
http://www.aic.nrl.navy.mil/galist/
-
The Genetic Algorithms Archive
http://www.alife.org/ -
International Society of Artificial Life
http://www.eleceng.ohio-state.edu/~passino/ICbook/ic_code.html
-
Kevin Passino’s Matlab-based GA software
http://www.cs.bham.ac.uk/Mirrors/ftp.de.uu.net/EC/clife/www/
-
The Hitch-Hiker’s Guide to Evolutionary
Computation
Prereqs:
Graduate Standing
Proficiency in Matlab
programming
Time: 4:00 - 6:00 M W
Instructor: Dr. Dan Simon
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Phone: |
216-687-5407 |
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Web Site: |
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Office: |
Stilwell Hall 343 |
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Lab: |
Stilwell Hall 306, 308, 326 |
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Office Hours: |
By appointment |
Feel free to email, call, or stop by my office any time and I’ll be happy
to help you if I’m available.
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Grading: |
Quizzes |
20% |
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Homework |
20% |
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Matlab |
20% |
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Midterm |
20% |
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Project |
20% |
Homework: In addition to written exercises, Matlab assignments will be given to demonstrate the theory in the text. You can work with others on homework, but identical homework assignments will be given a grade of zero. Late homework will not be accepted. Homework should be neat, the pages should be stapled with one staple in the upper left corner, and the problems should be in order. Any deviation from this format may result in a decrease of the homework grade.
Tests: Quizzes and Exams will be open-book and open-notes, but no electronic devices (e.g., calculators or laptops) will be allowed. No makeup quizzes or exams will be allowed without the prior permission of the instructor.
Project: Each student will be responsible for a research project based on genetic algorithms, evolutionary programming, or a related topic. The project can involve one of a number of different problems, such as
· The application of a GA to some realistic problem
· A theoretical enhancement of some aspect of GAs or EP
· The study and analysis of a journal or conference paper
· A review and analysis of early work in GAs or EP
· Analysis of the effects of various parameters / options on GA / EP performance
· Novel approaches to GAs or EP (e.g., simulations of the evolution of economic, governmental, or stellar systems)
· Some other topic related to GAs or EP
In all cases the project should
involve the writing of software and the presentation of simulation results. The
project will be graded on the basis of a written report and an oral report
(between 10 and 20 minutes) given on the last day of class. Appendix D of
Michalewicz’s book (see the reference list above) has a lot of good project
ideas and guidance.
Project
grade: Each of the
subtasks listed below is graded on a scale from 0 (low) to 4 (high). The written
report can be based on the template at http://academic.csuohio.edu/simond/courses/Report%20Template.doc
although this is not required.
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Task |
Subtask |
Points |
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Proposal
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16 |
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Abstract |
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Project
Description |
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Expected
Results |
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Timeline |
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Project |
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24 |
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Interest
Level |
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Motivation |
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Features |
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Success |
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Results |
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Scope |
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Written
Report |
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32 |
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Abstract |
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Introduction |
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Software
Listing |
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Figures
and Graphics |
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Organization |
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Clarity |
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Conclusion |
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References |
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Oral
Presentation |
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28 |
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Introduction |
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Correct
Length |
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Organization |
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Clarity |
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Visual
Aids |
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Audience
Interaction |
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Conclusion |
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Total |
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100 |
Important
Dates:
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Date |
Event |
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May 31 |
Holiday |
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July 5 |
Holiday |
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August 9 - 11 |
Project presentations |
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August 11 |
Written projects due |
Homework due dates and exam dates will be
determined by the instructor during the semester and announced in class. It is
the students’ responsibility to make sure they are aware of these dates. Late
project reports will not be accepted.
Grading
Scale:
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A |
93–100 |
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A minus |
90–92 |
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B plus |
87–89 |
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B |
83–86 |
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B minus |
80–82 |
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C |
70–79 |
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D |
60–69 |
Department of Electrical and Computer Engineering
Last Revised: June 2, 2004