Constraint Multi-objective Optimization based on Genetic Shuffled Frog Leaping Algorithm

Sun Lu-peng; Ma Ge

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Paper

Constraint Multi-objective Optimization based on Genetic Shuffled Frog Leaping Algorithm

In Proceedings of the Information Science and Management Engineering III ISME - Volume 1, 94-99, 2015 , Sanya, China

Authors: Sun Lu-peng and Ma Ge

Affiliation: Zhengzhou Normal University, China

Keyword(s): Shuffled Frog Leaping Algorithm, Multi-objective, Constraints.

Abstract: To solve the convergence problem of the constrained multi-objective optimization, combining the advantages of genetic algorithm and shuffled frog leaping algorithm，a method based on genetic shuffled frog leaping algorithm. To use the genetic operators and the packet improved shuffled frog leaping algorithm and avoid falling into local optimal, accelerating the convergence speed. Experiments show that the improved algorithm is efficient and reasonable, can reduce the execution time of the multi-objective optimization problem, improve the quality of optimal solution.

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Paper citation in several formats:

Lu-peng, S. and Ge, M. (2015). Constraint Multi-objective Optimization based on Genetic Shuffled Frog Leaping Algorithm. In Proceedings of the Information Science and Management Engineering III - ISME; ISBN 978-989-758-163-2, SciTePress, pages 94-99. DOI: 10.5220/0006019700940099

@conference{isme15,
author={Sun Lu{-}peng. and Ma Ge.},
title={Constraint Multi-objective Optimization based on Genetic Shuffled Frog Leaping Algorithm},
booktitle={Proceedings of the Information Science and Management Engineering III - ISME},
year={2015},
pages={94-99},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006019700940099},
isbn={978-989-758-163-2},
}

TY - CONF

JO - Proceedings of the Information Science and Management Engineering III - ISME
TI - Constraint Multi-objective Optimization based on Genetic Shuffled Frog Leaping Algorithm
SN - 978-989-758-163-2
AU - Lu-peng, S.
AU - Ge, M.
PY - 2015
SP - 94
EP - 99
DO - 10.5220/0006019700940099
PB - SciTePress