Evolutionary Computing - BBL 610E

Lecturer	Asst. Prof. Dr. A. Şima (Etaner) Uyar
Schedule	Fridays 09:30 - 12:30
Classroom	EEB 4300

Announcements

Final exam: May 30th, 9:00-11:00, classroom Z4.
You can use the Springer LNCS series Word or Latex templates for your reports. You can find these at this link. You can also use the IEEE Transactions styles which you can download from this link.
Reports for your term projects are due 06.June.2011 until 10:00 am. Please use the Ninova system to submit your reports. The system will ONLY accept pdf files.
You can submit your updated source codes through the the Ninova system until 10:00 am on the 6th of June.
No class on the 29th of April. You are advised to work on your term projects during that time.
Program codes for the term project is due 13.May.2011 until 23:55. Please use the Ninova system to submit your program codes.
Presentation files for the term project are due 12.May.2011 until 23:55. Please use the Ninova system to submit your presentations.
You will be expected to give a short presentation of your study on the 13th of May during class. Your project presentations in class should NOT be longer than 10 minutes.
Your project reports will be prepared in the form of an academic paper. These reports will be evaluated based on the criteria at this link. It is advised that you take these into consideration while preparing your report.
Your reports (papers) should be your own work and must not be based on only one paper or study you find in literature. Any copy/paste parts or direct uses without a reference, even if it is only a few sentences, will be treated as plagiarism and you will receive a 0 for the whole term project grade.

Tentative Topics

Evolutionary algorithms

Genetic algorithms
Genetic programming
Evolutionary strategies
Memetic algorithms
Differential evolution

Constraint handling 'n EAs
Fitness landscape analys's
Working with EAs

Theoretical framework

Experimental design
Output analysis
Benchmark functions

Multiobjective EAs
EAs for dynamic environments
Handling noise and uncertainties
Fitness approximation
Parallelization
Hybridization
Application areas

Tentative Weekly Schedule

Topic

Introduction to Course

Introduction to Search and Optimization

Stochastic Local Search

Genetic Algorithms

Working with EC

Assesment

Midterm	%20
Final Exam ***	%40
Term Project (implementation)	%20
Term Project (report and presentation)	%20

*** In order to qualify to take the final exam the following are required:
- Minimum 70% attendance
- Submission of term project (both implementation and report)

Reference Books

Introduction to Evolutionary Computing, A. E. Eiben, J. E. Smith, Springer, 2003.
Genetic Algorithms + Data Structures = Evolution Programs, Z. Michalewicz, Springer, 1999.
Differential Evolution: A Practical Approach to Global Optimization, K. V. Price, R. M. Storn, J. A. Lampinen, Springer, 2005.
Estimation of Distribution Algorithms, P. Larranaga, J. A. Lozano, Kluwer, 2002.
Experimental Research in Evolutionary Computation, T. Bartz-Beielstein, Springer, 2006.
Evolutionary Algorithms for Solving Multi-Objective Problems, C. A. Coello Coello, G. B. Lamont, D. A. Van Veldhuizen, Springer, 2007.
Evolutionary Optimization in Dynamic Environments, J. Branke, Kluwer, 2002.
Parallel Evolutionary Computations, N. Nedjah, El Alba, L. de Macedo Mourelle, Springer,2006.