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Training approaches in neural enhancement for multiobjective optimization

Published: 28 March 2008 Publication History

Abstract

In previous work, a neural network was used to increase the number of solutions found by an evolutionary multiobjective optimization algorithm. In this paper, various approaches are applied in the training of the neural network to determine whether an approach exists that can provide reasonable results in a reasonable time. To this end, two heuristic training algorithms are developed. When evaluated on a suite of ten benchmark mutliobjective optimization problems, these heuristic techniques perform very well and, on average, produce many more solutions than the evolutionary multiobjective optimization approach alone.

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C. A. C. Coello. 20 years of evolutionary multi-objective optimization: What has been done and what remains to be done. In G. Y. Yen and D. B. Fogel, editors, Computational Intelligence: Principles and Practice, pages 73--88. IEEE Computational Intelligence Society, 2006.
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E. Zitzler, M. Laumanns, and S. Bleuler. A tutorial on evolutionary multiobjective optimization. In Workshop on Multiple Objective Metaheuristics (MOMH 2002), Berlin, Germany, 2002. Springer-Verlag.

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cover image ACM Other conferences
ACMSE '08: Proceedings of the 46th annual ACM Southeast Conference
March 2008
548 pages
ISBN:9781605581057
DOI:10.1145/1593105
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 March 2008

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  1. genetic algorithms
  2. multiobjective optimization
  3. neural networks

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ACM SE08
ACM SE08: ACM Southeast Regional Conference
March 28 - 29, 2008
Alabama, Auburn

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