COURSE SYLLABUS AND OUTLINE
SWENG 584
GENETIC ALGORITHMS
|
Walter Cedeño |
Spring I, 2007 |
|
Tuesdays & Thursdays 6-9pm |
Penn State, Great Valley |
|
(610) 458-5264 (W) |
(610) 648-3277 |
The purpose of this course is to introduce the students to the applications of Genetic Algorithms (GAs) to problems in Engineering and Science. The first part of the course will focus on introductory material to Genetic Algorithms and the field of Evolutionary Computation (EC). Specifically, we will describe the classical and steady state Genetic Algorithms and show different types of genetic operators and their applications. Then we will introduce the concept of schemata and how it is used to model genetic algorithms. The second part of the course will present different applications of genetic algorithms. Some of the application areas to be covered are; multimodal function optimization, multi-objective problems, combinatorial optimization problems, biology and chemistry applications, and artificial neural networks.
The course will consist of lecture, demos, and paper reviews. Lectures will serve as the vehicle to introduce new information to the students. Demos will be use to enforced the material given in lectures and to show work from researchers in the field. Paper reviews will be use to investigate the application of genetic algorithms to practical problems. Participation is encouraged during the class.
As part of the course, the students will work on a project with the goal of applying GAs to a problem selected by the professor. Teams of two or three students will be created for each project. During the second part of the course, each team will provide an informal description of the problem and how the team plans to apply GAs to it. This exercise will help the team gain a better understanding of the problem and the GA techniques to use for it. Input from the class will provide the team with valuable ideas for the project and potentially provide direction on GA operators that will work for the problem.
Textbook: Introduction to Evolutionary Computing, Eiben, A. E. & Smith, J. E.,Springer, 2003, ISBN 3-540-40184-9.
Other References (NOT required):
The outline of the course is as follows:
Day 1: Introduction to EC (Chapters 1-2)
Day 2-4: Genetic Algorithms (Chapters 3, 8)
Project Topic Oral Presentation (Second half of
Day 3)
Day 5: Schemata and GAs (Sections 11.1-11.2)
Project Round Table
Day 6: Multimodal & Multi-objective Problems (Chapter 9)
Day 7: Midterm and Project Round Table
Day 8: Constraint Handling Problems (Chapter 12)
Day 9: Genetic Programming (Chapter 6)
Project Round Table
Day 10: Evolution Strategies & Evolutionary Programming (Chapters 4-5)
Day 11: Learning Classifiers Systems (Chapter 7)
Project Round Table
Day 12: Memetic Algorithms (Chapter 10)
Day 13: Oral Presentation
Day 14: Final & Paper due
Tools and demo applications to be use in class.
"Academic integrity is the pursuit of scholarly activity free from fraud and deception and is an educational objective of this institution. Academic dishonesty includes, but is not limited to, cheating, plagiarizing, fabricating of information or citations, facilitating acts of academic dishonesty by others, having unauthorized possession of examinations, submitting work for another person or work previously used without informing the instructor, or tampering with the academic work of other students. At the beginning of each course it is responsibility of the instructor to provide a statement clarifying the application of academic integrity to that course". (1989-90 Policies and Rules for Students, p.25).
DISABILITY STATEMENT:
The Pennsylvania State University encourages qualified persons with disabilities to participate in its programs and activities. If you anticipate needing any type of accommodation or have questions about the physical access provided, please contact Kathy Mingioni at 610-648-3315 in advance of your participation or visit.
SECURITY PLAN:
In the event of an emergency of any kind, you are advised to proceed to an agreed upon meeting point in a safer location - probably in the car park area. If you need special consideration in evacuating the classroom, please inform your instructor who will attempt to accommodate your special needs.
Emergency Evacuation Exercises or Actual Emergency Events:
Periodic fire/evacuation exercises are conducted in all occupied PSU Great Valley buildings. Every PSU Great Valley faculty, staff, and student is expected to exit the building and remain outside until the drill or actual event is completed. Drills are a safe opportunity to test the building emergency plan, insure that the fire alarm is working properly, and allows every employee a chance to experience the procedures.
Guidelines in the Event of a Drill or Emergency: