Chaotic Cuckoo Search Algorithm for Solving Unmanned Combat Aerial Vehicle Path Planning Problems-Reference-Cited by-同舟云学术

Chaotic Cuckoo Search Algorithm for Solving Unmanned Combat Aerial Vehicle Path Planning Problems

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 11th International Conference on Machine Learning and Computing - ICMLC '19
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Author:

Pan Jeng-Shyang¹,Liu Jenn-Long²,Hsiung Shou-Cheng³

Affiliation:

1. College of Information Science and Engineering, Fujian University of Tech., Fujian, China

2. Department of Information Management, I-Shou University, Kaohsiung, Taiwan

3. Department of Industrial Management, I-Shou University, Kaohsiung, Taiwan

Publisher

ACM Press

Reference24 articles.

1. Yang, X. S. and Deb, S. 2009. Cuckoo search via Lévy flights. In Proceedings of World Congress on Nature & Biologically Inspired Computing (Coimbatore, India, December 09--11, 2009), IEEE Press, Piscataway, NJ. 210--214.

2. Yang, X. S. and Deb, S. 2010. Engineering optimisation by cuckoo search. International Journal of Mathematical Modelling and Numerical Optimisation, 1, 4 (Dec. 2010) 330--334.

3. Civicioglu, P. and Besdok E. 2013. A conceptual comparison of the cuckoo-search, particle swarm optimization, differential evolution and artificial bee colony algorithms. Artificial Intelligence Review, 39, 4(April 2013), 315--346.

4. Clerc M. and Kennedy J. 2002. The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. on Evolutionary Computation, 6, 1 (Aug. 2002), 58--73.

5. Price K., Storn R., and Lampinen, J. 2005. Differential evolution: a practical approach to global optimization. Natural Computing Series, Springer, Berlin, Germany.

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