How
to Apply Genetic Algorithm Successfully
Tutorial
on Genetic Algorithm and Evolutionary Computation
4
March 2013
Prabhas
Chongstitvatana
Chulalongkorn
University
What
is EC (power point presentation)
EC
is a probabilistic search procedure to obtain solutions starting from a
set of candidate solutions, using improving operators to "evolve"
solutions. Improving operators are inspired by natural evolution.
Survival
of the fittest.
The
objective function depends on the problem.
EC
is not a random search.
Examples
of application of EC
<necsec8.pdf>
pp.14-19, 24-25.
Other Form of EC beside GA
GP
flowchart
Developmental
method creation
of a program circuit-layout
Parameterization controller high-pass-filter
EC
as inventor (invention machine)
Modern
GA
Estimation
of Distribution Algorithms
Building
Blocks Identification <current-ec.ppt>
p.11-15
Coincidence Algorithm
Example of EC applications
lead
free solder <current-ec.ppt>
p.6-10.
Biped
walker video <biped.avi>
Demonstration
Session
workbook
program
used in the session
<zip file 3360 Kbytes>
My
website
www.cp.eng.chula.ac.th/faculty/pjw/
my
email address: prabhas at chula dot ac dot th
Introductory
material
Whitley,
D., "Genetic algorithm tutorial", www.cs.colostate.edu
/~genitor/MiscPubs/tutorial.pdf (local
here)
Goldberg,
D., Genetic algorithms, Addison-Wesley, 1989.
Ponsawat,
J. and Chongstitvatana, P., "Solving 3-dimensional bin packing by modified
genetic algorithms", National Computer Science and Engineering Conference,
Thailand, 2003.
Chaisukkosol,
C. and Chongstitvatana, P., "Automatic synthesis of robot programs for a
biped static walker by evolutionary computation", 2nd Asian Symposium on
Industrial Automation and Robotics, Bangkok, Thailand, 17-18 May 2001,
pp.91-94.
Aporntewan,
C. and Chongstitvatana, P., "Building block identification by simultaneity
matrix for hierarchical problems", Genetic and Evolutionary Computation
Conference, Seattle, USA, 26-30 June 2004, Proc. part 1, pp.877-888.
Puncreobutr,
C., Lohwongwatana, B., and Chongstitvatana, P., "Genetic Programming
Approach to Determining Thermal Properties of Lead-free Solder Alloys,"
Proc. of National Computer Science and Engineering Conference, Bangkok,
Thailand, November 4-6, 2009.
Introductory
material of EDAs
Goldberg,
D., Design of Innovation, 2002.
Pelikan
et al. (2002). A survey to optimization by building and using
probabilistic models. Computational optimization and applications, 21(1).
Larraaga
& Lozano (editors) (2001). Estimation of distribution algorithms: A
new tool for evolutionary computation. Kluwer.
Prabhas
Chongstitvatana, Warin Wattanapornprom, Panuwat Olanviwitchai, Ronnachai
Sirovetnukul, Noppon Kampirom and Parames Chutima, invited paper,
"Coincidence Algorithm for Combinatorial Optimisation and Its
Applications," Proc. of Electrical Engineering Conference (33th),
Chiangmai, Thailand, 1-3 Dec. 2010.
Program
code, ECGA, BOA, and BOA with decision trees/graphs http://www-illigal.ge.uiuc.edu/
For
more materials please visit my lecture: 2110742 Evolutionary Computation
www.cp.eng.chula.ac.th/faculty/pjw/teaching/ec/ec2012/index-ec.htm
COIN
at my homepage www.cp.eng.chula.ac.th/faculty/pjw/project/coin/index-coin.htm
Acknowledgedment
My
students' team (2010)
