An agent-based hyper-heuristic approach to combinatorial optimization problems
This paper introduces a framework based on multi-agent system for solving problems of combinatorial optimization. The framework allows running various meta-heuristic algorithms simultaneously. By the collaboration of various meta-heuristics, we can achieve better results in more classes of problems....
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Published in | 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems Vol. 3; pp. 428 - 434 |
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Main Author | |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.10.2010
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Subjects | |
Online Access | Get full text |
ISBN | 9781424465828 1424465826 |
DOI | 10.1109/ICICISYS.2010.5658624 |
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Abstract | This paper introduces a framework based on multi-agent system for solving problems of combinatorial optimization. The framework allows running various meta-heuristic algorithms simultaneously. By the collaboration of various meta-heuristics, we can achieve better results in more classes of problems. Our hyper-heuristic approach is defined as a high-level search in algorithm space implemented within multi-agent system. |
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AbstractList | This paper introduces a framework based on multi-agent system for solving problems of combinatorial optimization. The framework allows running various meta-heuristic algorithms simultaneously. By the collaboration of various meta-heuristics, we can achieve better results in more classes of problems. Our hyper-heuristic approach is defined as a high-level search in algorithm space implemented within multi-agent system. |
Author | Malek, Richard |
Author_xml | – sequence: 1 givenname: Richard surname: Malek fullname: Malek, Richard email: malekric@fel.cvut.cz organization: Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University, Prague, Czech Republic |
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Snippet | This paper introduces a framework based on multi-agent system for solving problems of combinatorial optimization. The framework allows running various... |
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SubjectTerms | combinatorial optimization Genetic algorithms Genotypes Heuristic algorithms hybrid approach hyper-heuristic meta-heuristic algorithm Metaheuristics multi-agent system Multi-agent systems Oral communication Phenotypes Search problems Sequential analysis Space exploration |
Title | An agent-based hyper-heuristic approach to combinatorial optimization problems |
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