MPI-INF Logo
Publications

Server    domino.mpi-inf.mpg.de

Proceedings Article, Paper
@InProceedings
Beitrag in Tagungsband, Workshop

Author, Editor
Author(s):
Doerr, Benjamin
Jansen, Thomas
Sudholt, Dirk
Winzen, Carola
Zarges, Christine		dblp
dblp
dblp
dblp
dblp
Not MPG Author(s):
Jansen, Thomas
Sudholt, Dirk
Zarges, Christine
Editor(s):
Schaefer, Robert
Cotta, Carlos
Kolodziej, Joanna
Rudolph, Günter		dblp
dblp
dblp
dblp
Not MPII Editor(s):
Schaefer, Robert
Cotta, Carlos
Kolodziej, Joanna
Rudolph, Günter
BibTeX cite key*:
DoerrJSWZ10
Title, Booktitle
Title*:
Optimizing Monotone Functions Can Be Difficult
Booktitle*:
Parallel Problem Solving from Nature - PPSN XI. - Pt. 1
Event, URLs
Conference URL::
http://home.agh.edu.pl/~ppsn/
Downloading URL:
http://dx.doi.org/10.1007/978-3-642-15844-5_5
Event Address*:
Krakow, Poland
Language:
English
Event Date*
(no longer used):
Organization:
Event Start Date:
11 September 2010
Event End Date:
15 September 2010
Publisher
Name*:
Springer
URL:
http://www.springer.com/computer/lncs?SGWID=0-164-0-0-0
Address*:
Berlin
Type:
Vol, No, Year, pp.
Series:
Lecture Notes in Computer Science
Volume:
6238
Number:
Month:
September
Pages:
42-51
Year*:
2010
VG Wort Pages:
27
ISBN/ISSN:
978-3-642-15843-8
Sequence Number:
DOI:
10.1007/978-3-642-15844-5_5
Note, Abstract, ©
(LaTeX) Abstract:
Extending previous analyses on function classes like linear functions, we analyze how the simple (1+1) evolutionary algorithm optimizes pseudo-Boolean functions that are strictly monotone.
Contrary to what one would expect, not all of these functions are easy to optimize. The choice of the constant $c$ in the mutation probability $p(n) = c/n$ can make a decisive difference.

We show that if $c < 1$, then the \EA finds the optimum of every such function in $\Theta(n \log n)$ iterations. For $c=1$, we can still prove an upper bound of $O(n^{3/2})$.
However, for $c > 33$, we present a strictly monotone function such that the \EA with overwhelming
probability does not find the optimum within $2^{\Omega(n)}$
iterations. This is the first time that we observe that a constant factor change of the mutation probability changes the run-time by more than constant factors.
Download
Access Level:
Internal

Correlation
MPG Unit:
Max-Planck-Institut für Informatik
MPG Subunit:
Algorithms and Complexity Group
Appearance:
MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort



BibTeX Entry:

@INPROCEEDINGS{DoerrJSWZ10,
AUTHOR = {Doerr, Benjamin and Jansen, Thomas and Sudholt, Dirk and Winzen, Carola and Zarges, Christine},
 EDITOR = {Schaefer, Robert and Cotta, Carlos and Kolodziej, Joanna and Rudolph, G{\"u}nter},
 TITLE = {Optimizing Monotone Functions Can Be Difficult},
 BOOKTITLE = {Parallel Problem Solving from Nature - PPSN XI. - Pt. 1},
 PUBLISHER = {Springer},
 YEAR = {2010},
 VOLUME = {6238},
 PAGES = {42--51},
 SERIES = {Lecture Notes in Computer Science},
 ADDRESS = {Krakow, Poland},
 MONTH = {September},
 ISBN = {978-3-642-15843-8},
 DOI = {10.1007/978-3-642-15844-5_5},
}

Entry last modified by Manuel Lamotte-Schubert, 03/21/2011
Hide details for Edit History (please click the blue arrow to see the details)Edit History (please click the blue arrow to see the details)

Editor(s)
[Library]		Created
09/28/2010 14:48:47
Revisions
4.
3.
2.
1.
0.		Editor(s)
Manuel Lamotte-Schubert
Anja Becker
Carola Winzen
Anja Becker
Anja Becker		Edit Dates
21.03.2011 08:40:56
14.02.2011 13:15:42
01/04/2011 10:48:42 AM
03.01.2011 13:18:31
09/28/2010 02:48:47 PM