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Author, Editor

Author(s):

Kötzing, Timo
Neumann, Frank
Röglin, Heiko
Witt, Carsten

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Not MPG Author(s):

Röglin, Heiko
Witt, Carsten

Editor(s):

Dorigo, Marco
Birattari, Mauro
Di Caro, Gianni A.
Doursat, René
Engelbrecht, Andries P.
Floreano, Dario
Gambardella, Luca Maria
Groß, Roderich
Sahin, Erol
Sayama, Hiroki
Stützle, Thomas

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Not MPII Editor(s):

Dorigo, Marco
Birattari, Mauro
Di Caro, Gianni A.
Doursat, René
Engelbrecht, Andries P.
Floreano, Dario
Gambardella, Luca Maria
Groß, Roderich
Sahin, Erol
Sayama, Hiroki
Stützle, Thomas

BibTeX cite key*:

Koe-Neu-Roe-Wit:c:10:ACOTSP

Title, Booktitle

Title*:

Theoretical Properties of Two ACO Approaches for the Traveling Salesman Problem

Booktitle*:

Swarm Intelligence : 7th International Conference, ANTS 2010

Event, URLs

URL of the conference:


URL for downloading the paper:

http://dx.doi.org/10.1007/978-3-642-15461-4_28

Event Address*:

Brussels, Belgium

Language:

English

Event Date*
(no longer used):


Organization:


Event Start Date:

15 December 2010

Event End Date:

15 December 2010

Publisher

Name*:

Springer

URL:


Address*:

Berlin

Type:


Vol, No, Year, pp.

Series:

Lecture Notes in Computer Science

Volume:

6234

Number:


Month:


Pages:

324-335

Year*:

2010

VG Wort Pages:


ISBN/ISSN:

978-3-642-15460-7

Sequence Number:


DOI:

10.1007/978-3-642-15461-4_28



Note, Abstract, ©


(LaTeX) Abstract:

Ant colony optimization (ACO) has been widely used for different combinatorial optimization problems. In this paper, we investigate ACO algorithms with respect to their runtime behavior for the traveling salesperson problem (TSP). We present a new construction graph and show that it has a stronger local property than one commonly used for constructing solutions of the TSP. Our rigorous runtime analyses for two ACO algorithms, based on these two construction procedures, show that they achieve a good approximation in expected polynomial time on random instances.
Furthermore, we point out in which situations our algorithms get trapped in local optima and show where the use of the right amount of heuristic information is provably beneficial.



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{Koe-Neu-Roe-Wit:c:10:ACOTSP,
AUTHOR = {K{\"o}tzing, Timo and Neumann, Frank and R{\"o}glin, Heiko and Witt, Carsten},
EDITOR = {Dorigo, Marco and Birattari, Mauro and Di Caro, Gianni A. and Doursat, Ren{\'e} and Engelbrecht, Andries P. and Floreano, Dario and Gambardella, Luca Maria and Groß, Roderich and Sahin, Erol and Sayama, Hiroki and St{\"u}tzle, Thomas},
TITLE = {Theoretical Properties of Two ACO Approaches for the Traveling Salesman Problem},
BOOKTITLE = {Swarm Intelligence : 7th International Conference, ANTS 2010},
PUBLISHER = {Springer},
YEAR = {2010},
VOLUME = {6234},
PAGES = {324--335},
SERIES = {Lecture Notes in Computer Science},
ADDRESS = {Brussels, Belgium},
ISBN = {978-3-642-15460-7},
DOI = {10.1007/978-3-642-15461-4_28},
}


Entry last modified by Anja Becker, 01/11/2011
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Editor(s)
[Library]
Created
12/15/2010 11:54:47 AM
Revision
1.
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Editor
Anja Becker
Timo Kötzing


Edit Date
11.01.2011 13:26:50
12/15/2010 11:54:47 AM