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Author, Editor

Author(s):

Neumann, Frank
Witt, Carsten

dblp
dblp

Not MPG Author(s):

Witt, Carsten

Editor(s):





BibTeX Citekey*:

NeuWittMST2006

Language:

English

Title, Institution

Title*:

Ant Colony Optimization and the Minimum Spanning Tree Problem

Institution*:

Electronic Colloquium on Computational Complexity

Publishers or Institutions Address*:

http://eccc.hpi-web.de/eccc/

Type:

Technical Report

No, Year, pp.,

Number*:

TR06-143

Pages*:

12

Month:

November

VG Wort
Pages*:


Year*:

2006

ISBN/ISSN:






DOI:




Note, Abstract, ©

Note:


(LaTeX) Abstract:

Ant Colony Optimization (ACO) is a kind of randomized search heuristic that has become very popular for solving
problems from combinatorial optimization. Solutions for a given problem are constructed by a random walk on a so-called construction graph. This random walk can be influenced by heuristic information about the problem. In contrast to many
successful applications, the
theoretical foundation of this kind of randomized search heuristic is rather weak. Theoretical investigations with respect to the runtime behavior of ACO algorithms have been started only recently for the optimization of pseudo-boolean functions.

We present the first comprehensive rigorous analysis
of a simple ACO algorithms for a combinatorial optimization problem. In our investigations we consider the minimum spanning tree problem and examine the effect of two
construction graphs with respect to the runtime behavior.
The choice of the construction graph in an ACO algorithm seems to be crucial for the success of such an algorithm.
First, we take the input graph itself as the construction graph and analyze the use of a construction procedure that is similar to Broder's algorithm for choosing a spanning tree uniformly at random. After that, a more incremental construction procedure is analyzed. It turns out that this procedure is superior to the Broder-based algorithm and produces additionally in a constant number of iterations a minimum spanning tree if the influence of the heuristic information is large enough.

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Access Level:

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Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Algorithms and Complexity Group

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MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort


BibTeX Entry:
@TECHREPORT{NeuWittMST2006,
AUTHOR = {Neumann, Frank and Witt, Carsten},
TITLE = {Ant Colony Optimization and the Minimum Spanning Tree Problem},
YEAR = {2006},
TYPE = {Technical Report},
INSTITUTION = {Electronic Colloquium on Computational Complexity},
NUMBER = {TR06-143},
PAGES = {12},
ADDRESS = {http://eccc.hpi-web.de/eccc/},
MONTH = {November},
}


Entry last modified by Regina Kraemer, 07/10/2014
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Editor(s)
[Library]
Created
02/23/2007 10:27:22 AM
Revisions
2.
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Editor(s)
Regina Kraemer
Frank Neumann
Frank Neumann

Edit Dates
04/17/2007 11:49:17 AM
02/23/2007 10:31:23 AM
02/23/2007 10:27:22 AM

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