CS 571: Evolutionary Computation
Instructor: Jugal Kalita
- Syllabus Syllabus, Text book, Grading
- Lecture 1 (1/22): Discussion of syllabus, grading scheme, etc.
- Lectures 2 and 3 (1/27 and 1/29): We covered Chapter 1 (Introduction to optimization) in the Haupt and Haupt text. We also covered Chapters 13 (1-D unconstrained optimization), Chapter 14 (multi-dimensional unconstrained optimization), Chapter 15 (constrained optimization) of Chapra and Canale's Numerical Methods for Engineers. Presentation on Optimization.
- Lectures 4 and 5 (2/3 and 2/5): We discussed protein function (about.com), the physical basis of heredity (Chapter 1 of Genetics, Fourth Edition by Elrod and Stansfield), Evolution of life on earth (a handout form Barton et al. 2007), Mutation and Evolution. The book we referred to was Evolution by Barton, Briggs, Eisen, Goldstein and Patel, published by Cold Spring Harbor Laboratory Press. We also followed the presenation on Evolution at the University of California at Berkeley.
- Lectures 6 and 7: The students presented proposals for their semester projects.
- Lectures 8 and 9: We discussed Chapter 2 (The binary genetic algorithm) of the Haupt and Haupt text. We also discussed Chapter 3 (Data normalization) from Artificial Neural Networks: An Introduction by Kevin L. Priddy and Paul E. Keller. Presentation on Binary Genetic Algorithms. Read the guidelines for writing a better paper based on the evaluation of the proposal documents.
- Lecture 10 (2/24): Real-valued GA. Here is the class presentation. We also looked at an MS thesis by A.A. Adewuya at MIT (1996).
- Lectures 11 and 12 (2/26, 3/3): We are discussing Chapter 4 of Haupt and Haupt (Basic Applications). We are also going over the paper titled "Evolutionary Visual Art and Design" from "Evolutionary Visual Art and Design". You may have to be on campus to access this file. We also looked briefly at the Ph.D. thesis titled "Computer Graphic Control over Human Face and Head Appearance, Genetic Optimisation of Perceptual Characteristics, Michigan State University, 1998. You should be able to find this thesis by searching on Google. Also, looked at mzlabs.com for some examples of genetic art.
- Lectures 12, 13, 14 (3/5, 3/17, 3/19): Similarity templates (Schemata), Mathematical Foundations of Genetic Algorithms. Chapters 1 and 2 of Goldberg's "Genetic Algorithsm in Search, Optimization and Machine Learning" text. We also looked at "Genetic Algorithm Tutorial" by D. Whitley. Here is the class presentation.
- Lectures 15, 16: Students presented updates on their projects: Midterm I presentations
- Lectures 17 and 18 (3/31, 4/2): We studied Appendix E: Partition Coefficient Transforms for Problem-Coding Analysis from Goldberg's text. We also looked at Walsh functions and how they can be used for theoretical analysis of genetic algorithms. We also discussed the paper "Deception Considered Harmful" by Grefenstette, 1993. We briefly noted what Messy GAs are by looking at Section 2.4 of Harik's Ph.D. dissertation.
- Lectures 19, 20 (4/7, 4/9): Multi-objective optimization: We looked at the "Multiobjective Optimization" section in Chapter 5 of Goldberg's book, Section 5.2 of Haupt and Haupt's book. We spent quite a bit of time looking at the paper titled "A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II" by Deb, Pratap, Agrawal and Meyarivan, IEEE Transactions of Evolutionary Computation, Vol 6, No 2, April 2002, pp. 182-197.
- Lectures 21, 22: Second midterm update presentations by students.
- Lectures 23, 24 (4/21, 4/23): We looked at Section 5.3 of Haupt and Haupt: Hybrid GA. We then discussed the paper titled "Microgenetic Algorithms as Generalized Hill-Climbing Operators for GA Optimization" by Kazarlis, Papadakis, Theocharis and Petridish.
- Lectures 24, 25 (4/23, 4/25): We looked at Section 5.10 of Haupt and Haupt: Permutation Problems. We studied the paper titled "A random-key genetic algorithm for the generalized traveling salesman problem" by Synder and Daskin.
- Lectures 25, 26 (4/28, 4/30): Particle Swarm Optimization (Section 7.2 of Haupt and Haupt). We discussed the paper "Particle Swarm Optimization" by Kennedy and Eberhart.
- Lecture 27 (5/5): Ant Colony Optimization (Section 7.3 of Haupt and Haupt) and the paper titled "Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem" by Dorigo and Gambardella.
- Lecture 28 (5/7): We discussed the paper titled "Architecture for an Artificial Immune System" by Hofmeyr and Forrest from 2001.
- Lecture 29 (5/12): Each student presented his final findings for the individual class project.