Variable space diversity, crossover and mutation in MOEA solving many-objective knapsack problems-Reference-Cited by-同舟云学术

Variable space diversity, crossover and mutation in MOEA solving many-objective knapsack problems

Published:2012-04-15 Issue:4 Volume:68 Page:197-224
ISSN:1012-2443
Container-title:Annals of Mathematics and Artificial Intelligence
language:en
Short-container-title:Ann Math Artif Intell

Author:

Sato Hiroyuki,Aguirre Hernán,Tanaka Kiyoshi

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Artificial Intelligence

Link

http://link.springer.com/content/pdf/10.1007/s10472-012-9293-y.pdf

Reference33 articles.

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3. Aguirre, H., Tanaka, K.: Working principles, behavior, and performance of MOEAs on MNK-landscapes. Eur. J. Oper. Res. 181(3), 1670–1690 (2007)

4. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast elitist multi-objective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6, 182–197 (2002)

5. Zitzler, E., Laumanns, M., Thiele, L.: SPEA2: improving the strength Pareto evolutionary algorithm. TIK-Report, No.103 (2001)

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