Proceedings of the Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support

Proactive selection of metaheuristics based on knowledge of previous results

Authors
Alejandro Rosete-Suárez, Mailyn Moreno-Espino
Corresponding Author
Alejandro Rosete-Suárez
Available Online October 2013.
DOI
10.2991/.2013.14How to use a DOI?
Keywords
metaheuristic, agents, proactive behavior
Abstract

This paper presents two proactive algorithms that act as meta-metaheuristic agents: they decide which metaheuristic will be used to solve a new problem. These meta-metaheuristic agents operate in the environment of iterative work on optimizing problems, with the goal of selecting good metaheuristics to solve new problems. The information about previous results is converted into ex-plicit knowledge that is used by the meta-metaheuristic agents to decide the most adequate metaheuristics. This proactive decision is based on a fuzzy vector that de-scribes each problem. The proposal has been validated through experimentation with 28 functions on binary strings.

Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support
Series
Advances in Intelligent Systems Research
Publication Date
October 2013
ISBN
10.2991/.2013.14
ISSN
1951-6851
DOI
10.2991/.2013.14How to use a DOI?
Copyright
© 2013, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Alejandro Rosete-Suárez
AU  - Mailyn Moreno-Espino
PY  - 2013/10
DA  - 2013/10
TI  - Proactive selection of metaheuristics based on knowledge of previous results
BT  - Proceedings of the Fourth International Workshop on Knowledge Discovery, Knowledge Management and Decision Support
PB  - Atlantis Press
SP  - 111
EP  - 119
SN  - 1951-6851
UR  - https://doi.org/10.2991/.2013.14
DO  - 10.2991/.2013.14
ID  - Rosete-Suárez2013/10
ER  -