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IlliGAL New Technical Reports Announcement (December 2001)
The Illinois Genetic Algorithms Laboratory (IlliGAL) is pleased to
announce the publication of the following new technical reports and
software. Most IlliGAL technical reports, as well as reprints of
other publications, are available in hardcopy and can be ordered from
the IlliGAL librarian, (see below for ordering information). The
technical reports in this announcement are also available
electronically on our ftp and WWW servers (see the end of this
announcement for ftp and WWW access instructions).
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IlliGAL Report No 2001029
Evolutionary Algorithms + Graphical Models = Scalable Black-Box
Optimization
Pelikan, M., Sastry, K., Goldberg, D.E.
Abstract:
To solve a wide range of different problems, the research in
black-box optimization faces several important challenges. One of the
most important challenges is the design of methods capable of
automatically discovering the regularities in the problem and
utilizing these to ensure efficient and reliable search. This paper
discusses the Bayesian optimization algorithm (BOA) that uses
Bayesian networks to model promising solutions and guide exploration
of the search space. Using Bayesian networks in combination with
population-based genetic and evolutionary search allows the algorithm
to discover and utilize regularities in the form of a problem
decomposition. The paper analyzes the applicability of the methods
for learning Bayesian networks in context of genetic and evolutionary
search. In particular, the population sizing ensuring that BOA learns
a proper decomposition of the problem is analyzed. The paper
concludes that the combination of the two approaches in BOA yields a
robust, efficient, and accurate search.
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IlliGAL Report No 2001030
>From TwoMax to the Ising Model: Easy and hard symmetrical problems
Van Hoyweghen, C., Goldberg, D.E., Naudts, B.
Abstract:
The paper shows that there is a key dividing line between two types
of symmetrical problems: problems for which a genetic algorithm (GA)
benefits from the fact that genetic drift chooses between equally
good partial solutions, and problems for which all equally good
partial solutions have to be preserved to find an optimum. By
analyzing in detail the search process of a selectorecombinative GA
optimizing a TwoMax and comparing this search process with that of an
Ising model, the paper investigates the difference between these two
types of symmetrical problems. For the first type of problems,
naively adding a niching technique to the genetic algorithm makes the
problem harder to solve. For the last type of problems, niching is
necessary to find an optimum.
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RETRIEVAL/ORDERING:
The above IlliGAL reports and publications, along with other
publications and source code, are available electronically via FTP or
WWW, or as hardcopy directly from us:
FTP: ftp ftp-illigal.ge.uiuc.edu
login: anonymous
password: (your email address)
cd /pub/papers/IlliGALs (for reports) or
cd /pub/papers/Publications (for preprints) or
cd /pub/src (for GA and classifier system source code)
binary
get 99022.ps.Z (for example)
Please look at the README files for explanations of what the file
names mean. IlliGAL reports are all compressed postscript files.
WWW: To access the IlliGAL home page, open
http://www-illigal.ge.uiuc.edu/
HARDCOPY:
You can also order hardcopy versions of most IlliGAL publications
Use the order form in the web or request them directly
(by IlliGAL number or title) from the IlliGAL librarian:
Internet: library@illigal.ge.uiuc.edu Phone: 217/333-2346
Fax: 217/244-5705
Surface mail: IlliGAL Librarian
Department of General Engineering
117 Transportation Building
104 South Mathews Avenue
Urbana, IL 61801-2996, USA
When ordering hardcopy, please include your surface mail address!
Martin Pelikan
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Martin Pelikan
Illinois Genetic Algorithms Laboratory
University of Illinois at Urbana Champaign
117 Transportation Building
104 S. Mathews Avenue, Urbana, IL 61801
Tel: (217) 333-2346, FAX: (217) 244-5705
E-mail: pelikan@illigal.ge.uiuc.edu
WWW: http://www-illigal.ge.uiuc.edu/~pelikan/
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