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Stefan cel Mare
University of Suceava
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ROMANIA

Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  4/2018 - 6

Continuous Time Chaotic Systems for Whale Optimization Algorithm

TANYILDIZI, E. See more information about TANYILDIZI, E. on SCOPUS See more information about TANYILDIZI, E. on IEEExplore See more information about TANYILDIZI, E. on Web of Science, CIGAL, T. See more information about CIGAL, T. on SCOPUS See more information about CIGAL, T. on SCOPUS See more information about CIGAL, T. on Web of Science
 
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Download PDF pdficon (1,307 KB) | Citation | Downloads: 811 | Views: 1,973

Author keywords
artificial intelligence, chaos, computational intelligence, continuous time systems, whale optimization algorithm

References keywords
optimization(23), algorithm(12), chaos(11), chaotic(9), algorithms(9), systems(6), evolutionary(6), swarm(5), computation(5), applied(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-11-30
Volume 18, Issue 4, Year 2018, On page(s): 49 - 56
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.04006
Web of Science Accession Number: 000451843400006
SCOPUS ID: 85058817066

Abstract
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Discrete time chaotic systems are often used instead of random number arrays in order to improve the convergence properties of optimization algorithms and prevent them to get stuck on local solutions. In this study, discrete-time and continuous-time chaotic systems are employed to improve the performance of Whale Optimization Algorithm (WOA), for the first time. It is suggested to use continuous-time chaotic systems instead of discrete-time systems in some cases. Using 23 benchmark functions and two engineering problems, one-dimensional chaotic maps and continuous time chaotic systems were analyzed on WOA. The results show that especially in multidimensional problems the use of the continuous time chaotic system can improve the performance of the algorithm and provide faster convergence.


References | Cited By  «-- Click to see who has cited this paper

[1] B. Alatas, "Chaotic bee colony algorithms for global numerical optimization", Expert Systems with Applications, vol. 37, no. 8, pp. 5682-5687, 2010.
[CrossRef] [Web of Science Times Cited 402]


[2] X. Yang, S. Deb, "Engineering optimization by cuckoo search" International Journal of Mathematical Modelling and Numerical Optimization, vol. 1, no. 4, pp. 330-343, 2010.
[CrossRef]


[3] R. Eberhart, J. Kennedy. "A new optimizer using particle swarm theory", Micro Machine and Human Science, MHS'95., Proceedings of the Sixth International Symposium, pp. 39-43, 1995.
[CrossRef]


[4] M. Dorigo, M. Birattari, T. Stutzle. "Ant colony optimization", IEEE computational intelligence magazine, vol. 1, no.4, pp.28-39, 2006.
[CrossRef] [Web of Science Times Cited 1385]


[5] K. F. Man, K. S. Tang, S.Kwong. "Genetic algorithms: concepts and applications [in engineering design]", IEEE transactions on Industrial Electronics, vol. 43, no. 5, pp. 519-534, 1996.
[CrossRef] [Web of Science Times Cited 774]


[6] D. Karaboga, B. Basturk, "Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems", Foundations of fuzzy logic and soft computing, pp. 789-798, 2007.
[CrossRef] [Web of Science Times Cited 861]


[7] E. Tanyildizi, G. Demir, "Golden Sine Algorithm, A Novel Math-Inspired Algorithm", Advances in Electrical and Computer Engineering, vol. 17, no. 2, pp. 71-78, 2017.
[CrossRef] [Web of Science Times Cited 356]


[8] H. Joshi, S. Arora, "Enhanced grey wolf optimization algorithm for global optimization", Fundamenta Informaticae, vol. 153 no.3, pp.235-264, 2017.
[CrossRef] [Web of Science Times Cited 52]


[9] S. Mirjalili, A. Lewis, "The Whale Optimization Algorithm", Advances in Engineering Software, vol. 95, pp.51-67, 2016.
[CrossRef] [Web of Science Times Cited 6666]


[10] S. Mirjalili S., Mirjalili S. M., Lewis A. "Grey wolf optimizer", Advances in engineering software, vol. 69, pp.46-61, 2014.
[CrossRef] [Web of Science Times Cited 9353]


[11] N. Jayakumar, S. Subramanian, S. Ganesan, E.B. Elanchezhian, "Grey wolf optimization for combined heat and power dispatch with cogeneration systems", International Journal of Electrical Power & Energy Systems, vol.74, pp.252-264, 2016.
[CrossRef] [Web of Science Times Cited 155]


[12] R. E. Precup, R. C. David, E. M. Petriu, "Grey wolf optimizer algorithm-based tuning of fuzzy control systems with reduced parametric sensitivity", IEEE Transactions on Industrial Electronics, vol. 64 no.1, pp.527-534, 2017.
[CrossRef] [Web of Science Times Cited 217]


[13] L. Dos Santos Coelho, D. L. de Andrade Bernert, V. C. Mariani, "A chaotic firefly algorithm applied to reliability-redundancy optimization", Evolutionary Computation (CEC), IEEE Congress, pp. 517-521, 2011.
[CrossRef]


[14] B. Alatas, E. Akin, B. Ozer, "Chaos embedded particle swarm optimization algorithms", Chaos, Solitons & Fractals,vol. 40, no. 4, pp.1715-1734, 2009.
[CrossRef] [Web of Science Times Cited 356]


[15] L. S. Coelho, V. C. Mariani, "Use of chaotic sequences in a biologically inspired algorithm for engineering design optimization", Expert Systems with Applications, vol. 34, pp. 1905-1913, 2008.
[CrossRef] [Web of Science Times Cited 168]


[16] L. Y. Chuang, C. H. Yang, J. C. Li, "Chaotic maps based on binary particle swarm optimization for feature selection", Applied Soft Computing, vol. 11, no. 1, pp. 239-248,2011.
[CrossRef] [Web of Science Times Cited 167]


[17] Sayed G. I., Darwish A., Hassanien A. E. "A New Chaotic Whale Optimization Algorithm for Features Selection", Journal of Classification, vol. 35, pp. 1-45, 2018.
[CrossRef] [Web of Science Times Cited 81]


[18] E. Tanyildizi, T. Cigal, "Whale Optimization Algorithms with Chaotic Mapping", Firat University, Engineering Sciences Journal, vol. 29 , no. 1, pp. 307-317, 2017.

[19] F. Ozkaynak, "A novel method to improve the performance of chaos based evolutionary algorithms", Optik-International Journal for Light and Electron Optics, vol. 126, no.24, pp. 5434-5438, 2015.
[CrossRef] [Web of Science Times Cited 25]


[20] Hala S., Hamilton H. J., Domenici P., "Simulating the Bubble Net Hunting Behaviour of Humpback Whales: The BNH-Whale Algorithm", Canadian Conference on Artificial Intelligence, Springer, Cham, pp.40-45, 2016.
[CrossRef] [Web of Science Times Cited 1]


[21] R. Caponetto, L. Fortuna, S. Fazzino, M. G. Xibilia, "Chaotic sequences to improve the performance of evolutionary algorithms", IEEE transactions on evolutionary computation, vol. 7, no.3, pp. 289-304, 2003.
[CrossRef] [Web of Science Times Cited 381]


[22] H. Nozawa, "A neural network model as a globally coupled map and applications based on chaos", Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 2, no. 3, pp. 377-386, 1992.
[CrossRef] [Web of Science Times Cited 217]


[23] K. Fallahi, R. Raoufi, H. Khoshbin, "An application of Chen system for secure chaotic communication based on extended Kalman filter and multi-shift cipher algorithm", Communications in Nonlinear Science and Numerical Simulation, vol. 13, no. 4, pp. 763-781, 2008.
[CrossRef] [Web of Science Times Cited 56]


[24] L. O. Chua, C. W. Wu, A. Huang, G. Q. Zhong, "A universal circuit for studying and generating chaos", I. Routes to chaos. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol. 40, no. 10, pp. 732-744, 1993.
[CrossRef] [Web of Science Times Cited 368]


[25] T. Matsumoto, "Chaos in electronic circuits", Proceedings of the IEEE, vol. 75, no.8, pp.1033-1057, 1987.
[CrossRef] [Web of Science Times Cited 97]


[26] M. S. Tavazoei, M. Haeri, "Comparison of different one-dimensional maps as chaotic search pattern in chaos optimization algorithms", Applied Mathematics and Computation, vol. 187, no. 2, pp. 1076-1085, 2007.
[CrossRef] [Web of Science Times Cited 218]


[27] D. Yang, G. Li, G. Cheng, "On the efficiency of chaos optimization algorithms for global optimization", Chaos, Solitons & Fractals, vol. 34, no. 4, pp. 1366-1375, 2007.
[CrossRef] [Web of Science Times Cited 297]


[28] E. N. Lorenz, "Deterministic nonperiodic flow", Journal of the atmospheric sciences, vol. 20, no. 2, pp. 130-141, 1963.
[CrossRef]


[29] X. Yao, Y. Liu, G. Lin, "Evolutionary programming made faster", IEEE Transactions on Evolutionary computation, vol. 3, no. 2, pp. 82-102, 1999.
[CrossRef] [Web of Science Times Cited 2741]


[30] C. Worasucheep, "Solving constrained engineering optimization problems by the constrained PSO-DD", In Electrical Engineering/Electronics, Computer, Information Technology and Telecommunications. ECTI-CON. 5th International Conference, Vol. 1, pp. 5-8, 2008.
[CrossRef] [Web of Science Times Cited 13]


[31] S. Hassan, K. Kumar, C. D. Raj, K. Sridhar, "Design and optimization of pressure vessel using metaheuristic approach", Applied Mechanics and Materials, Trans Tech Publications, vol. 465, pp. 401-406, 2014.
[CrossRef] [Web of Science Times Cited 9]


[32] X. Hu, R. C. Eberhart, Y. Shi, "Engineering optimization with particle swarm", Swarm Intelligence Symposium, 2003. SIS'03. Proceedings of the 2003 IEEE, pp. 53-57, 2003.
[CrossRef] [Web of Science Times Cited 241]


[33] C. A. C. Coello, E. M. Montes, "Constraint-handling in genetic algorithms through the use of dominance-based tournament selection", Advanced Engineering Informatics, vol. 16, no. 3, pp. 193-203.
[CrossRef] [Web of Science Times Cited 630]


[34] [Online] Available: Temporary on-line reference link removed - see the PDF document

[35] M. Mahdavi, M. Fesanghary, E. Damangir, "An improved harmony search algorithm for solving optimization problems", Applied mathematics and computation, vol. 188, no. 2, pp. 1567-1579, 2007.
[CrossRef] [Web of Science Times Cited 1383]




References Weight

Web of Science® Citations for all references: 27,670 TCR
SCOPUS® Citations for all references: 0

Web of Science® Average Citations per reference: 769 ACR
SCOPUS® Average Citations per reference: 0

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-03-27 00:29 in 187 seconds.




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