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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
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ROMANIA

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


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  3/2017 - 11

Repeating Successful Movement Strategy for ABC Algorithm

KOCER, B. See more information about KOCER, B. on SCOPUS See more information about KOCER, B. on IEEExplore See more information about KOCER, B. on Web of Science
 
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Download PDF pdficon (1,377 KB) | Citation | Downloads: 660 | Views: 1,908

Author keywords
artificial intelligence, machine learning, evolutionary computation, particle swarm optimization, machine intelligence

References keywords
optimization(18), algorithm(18), artificial(13), colony(12), comput(8), jasoc(6), swarm(5), soft(5), search(5), jins(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2017-08-31
Volume 17, Issue 3, Year 2017, On page(s): 85 - 94
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.03011
Web of Science Accession Number: 000410369500011
SCOPUS ID: 85028548845

Abstract
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ABC is a well-known nature inspired algorithm. In short ABC algorithm mimics the foraging behavior of the bee colonies. ABC is very intensively worked algorithm. It has many variants. The base algorithm and most of the variants uses an update equation to improve the solutions. The update equation finds a feasible movement based on neighbor solutions and adds that movement to current to create a mutant solution. If the mutant solution is better than the original one then original solution is updated. None of the ABC variant use a successful movement again. In this work when a successful move found then it is used again. Proposed approach is applied to ABCVSS algorithm which is a recently proposed ABC variant and that modified ABCVSS algorithm (ABCVSSRSM) is tested on numerical benchmark functions and results compared the well-known ABC variants. Results show that proposed method is superior under multiple criteria.


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

[1] D. Karaboga, "An idea based on honey bee swarm for numerical optimization," Erciyes University, Kayseri, Turkey, Tech. Rep., TR06, 2005.

[2] J. Kennedy, R. Eberhart, "Particle swarm optimization," in 1995 IEEE international conference on neural networks proceedings, Vols. 1-6 pp. 1942-1948, 1995

[3] M. Dorigo, V. Maniezzo, A. Colorni, "Ant system: Optimization by a colony of cooperating agents," IEEE Transactions on Systems Man and Cybernetics Part B, Cybernetics, 26(1), 1996, pp. 29-41.
[CrossRef] [Web of Science Times Cited 6818] [SCOPUS Times Cited 9294]


[4] X. S. Yang, S. Deb, "Engineering optimization by cuckoo search," Int. J. Math. Model. Numer. Opt. 1, pp. 330-343, 2010

[5] X. S. Yang, "Firefly algorithm, stochastic test functions and design optimisation," International Journal of Bio-Inspired Computation, 2(2), pp. 78-84, 2010
[CrossRef] [Web of Science Times Cited 1462] [SCOPUS Times Cited 1806]


[6] Z. W. Geem, J. H. Kim, G. V. Loganathan, "A new heuristic optimization algorithm: Harmony search. Simulation," 76(2), pp. 60-68, 2001
[CrossRef] [Web of Science Times Cited 3738] [SCOPUS Times Cited 4691]


[7] Uymaz S. A. , Tezel G., Yel E., Artificial algae algorithm (AAA) for nonlinear global optimization, Applied Soft Computing, Volume 31, June 2015, pp. 153-171, ISSN 1568-4946,
[CrossRef] [Web of Science Times Cited 142] [SCOPUS Times Cited 156]


[8] H. M. Harmanani, F. Drouby, S. B. Ghosn, A parallel genetic algorithm for the open-shop scheduling problem using deterministic and random moves, International Journal of Artificial Intelligence, vol. 14, no. 1, pp. 130-144, 2016.

[9] Z. C. Johanyák, O. Papp, "A hybrid algorithm for parameter tuning in fuzzy model identification," Acta Polytechnica Hungarica, vol. 9, no. 6, pp. 153-165, 2012.

[10] R.-E. Precup, R.-C. David, E. M. Petriu, S. Preitl, M.-B. Radac, "Novel adaptive charged system search algorithm for optimal tuning of fuzzy controllers," Expert Systems with Applications, vol. 41, no. 4, pp. 1168-1175, 2014
[CrossRef] [Web of Science Times Cited 70] [SCOPUS Times Cited 76]


[11] A. Basgumus, M. Namda, R, G. Yilmaz, A. Altuncu, "Performance comparison of the differential evolution and particle swarm optimization algorithms in free-space optical communications systems," Advances in Electrical and Computer Engineering, vol. 15, no. 2, pp. 17-22, 2015.
[CrossRef] [Full Text] [Web of Science Times Cited 10] [SCOPUS Times Cited 11]


[12] B. Akay, D. Karaboga, "A modified artificial bee colony algorithm for real-parameter optimization," Inf. Sci. 192, pp. 120-142, 2012
[CrossRef] [Web of Science Times Cited 756] [SCOPUS Times Cited 930]


[13] G. Zhu, S. Kwong, "Gbest-guided artificial bee colony algorithm for numerical function optimization," Appl. Math. Comput. 217, pp. 3166-3173, 2010
[CrossRef] [Web of Science Times Cited 823] [SCOPUS Times Cited 1054]


[14] A. Banharnsakun, T. Achalakul, B. Sirinaovakul, "The best-so-far selection in artificial bee colony algorithm," Appl. Math. Comput. 11, pp. 2888-2901, 2011
[CrossRef] [Web of Science Times Cited 308] [SCOPUS Times Cited 375]


[15] A. Banharnsakun, B. Sirinaovakul, T. Achalakul, "The best-so-far ABC with multiple patrilines for clustering problems," Neurocomputing 116, pp. 355-366, 2013
[CrossRef] [Web of Science Times Cited 23] [SCOPUS Times Cited 25]


[16] W. Gao, S. Liu, L. Huang, "A global best artificial bee colony algorithm for global optimization," J. Comput. Appl. Math. 236 pp. 2741-2753, 2012
[CrossRef] [Web of Science Times Cited 313] [SCOPUS Times Cited 366]


[17] M. S. Kiran, O. Findik, "A directed artificial bee colony algorithm," Appl. Soft Comput. 26, pp. 454-462, 2015
[CrossRef] [Web of Science Times Cited 152] [SCOPUS Times Cited 184]


[18] W. Gao, S. Liu, "A modified artificial bee colony algorithm," Comput. Oper. Res. 39, pp. 687-697, 2012
[CrossRef] [Web of Science Times Cited 400] [SCOPUS Times Cited 531]


[19] D. Karaboga, B. Gorkemli, "A quick artificial bee colony (qABC) algorithm and its performance on optimization problems," Appl. Soft Comput. 23, pp. 227-238, 2014
[CrossRef] [Web of Science Times Cited 219] [SCOPUS Times Cited 261]


[20] N. Imanian, M.E. Shiri, P. Moradi, "Velocity based artificial bee colony algorithm for high dimensional continuous optimization problems," Eng. Appl. Artif. Intell. 36, pp. 148-163, 2014
[CrossRef] [Web of Science Times Cited 59] [SCOPUS Times Cited 65]


[21] W. Du, B. Li "Multi-strategy ensemble particle swarm optimization for dynamic optimization," Inform. Sci., 178 (15), pp. 3096-3109, 2008
[CrossRef] [Web of Science Times Cited 178] [SCOPUS Times Cited 212]


[22] R. Mallipeddi, S. Mallipeddi, P.N. Suganthan, "Ensemble strategies with adaptive evolutionary programming," Inform. Sci., 180 (9), pp. 1571-1581, 2010
[CrossRef] [Web of Science Times Cited 93] [SCOPUS Times Cited 107]


[23] R. Mallipeddi, P.N. Suganthan, "Ensemble of constraint handling techniques," IEEE Trans. Evolut. Comput., 14(4), pp. 561-579, 2010
[CrossRef] [Web of Science Times Cited 291] [SCOPUS Times Cited 344]


[24] R. Mallipeddi, P.N. Suganthan, Q.K. Pan, M.F. Tasgetiren, "Differential evolution algorithm with ensemble of parameters and mutation strategies," Appl. Soft Comput., 11(2), , pp. 1679-1696, 2011
[CrossRef] [Web of Science Times Cited 942] [SCOPUS Times Cited 1036]


[25] H. Wang, Z. Wu, S. Rahnamayan, H. Sun, Y. Liu, J. Pan, "Multi-strategy ensemble artificial bee colony algorithm," Inf. Sci. 279, pp. 587-603, 2014
[CrossRef] [Web of Science Times Cited 182] [SCOPUS Times Cited 223]


[26] M. S. Kiran, H. Hakli, M. Gunduz, H. Uguz, "Artificial bee colony algorithm with variable search strategy for continuous optimization," Information Sciences 300, pp. 140-157, 2010
[CrossRef] [Web of Science Times Cited 171] [SCOPUS Times Cited 200]


[27] W. Gao, S. Liu, L. Huang, "A novel artificial bee colony algorithm based on modified search equation and orthogonal learning," IEEE T. Syst. Man Cy. B, 2012,
[CrossRef] [Web of Science Times Cited 275] [SCOPUS Times Cited 328]


[28] P. N. Suganthan, N. Hansen, J.J. Liang, K. Deb, Y.-P. Chen, A. Auger, S. Tiwari, "Problem definitions and evaluation criteria for the CEC 2005 special session on real parameter optimization," Technical report, 2005005, ITT Kanpur, India, 2005.

[29] V. Muthiah-Nakarajan, M. M. Noel, "Galactic Swarm Optimization: A new global optimization metaheuristic inspired by galactic motion," Applied Soft Computing, Volume 38, January 2016, Pages 771-787, ISSN 1568-4946,
[CrossRef] [Web of Science Times Cited 89] [SCOPUS Times Cited 108]




References Weight

Web of Science® Citations for all references: 17,514 TCR
SCOPUS® Citations for all references: 22,383 TCR

Web of Science® Average Citations per reference: 584 ACR
SCOPUS® Average Citations per reference: 746 ACR

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 2022-11-22 16:05 in 282 seconds.




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