{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T04:54:14Z","timestamp":1770353654277,"version":"3.49.0"},"reference-count":26,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. &amp; Syst."],"published-print":{"date-parts":[[2019,10,1]]},"DOI":"10.1587\/transinf.2019edp7013","type":"journal-article","created":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T02:48:11Z","timestamp":1569898091000},"page":"1916-1924","source":"Crossref","is-referenced-by-count":3,"title":["Enhancing the Performance of Cuckoo Search Algorithm with Multi-Learning Strategies"],"prefix":"10.1587","volume":"E102.D","author":[{"given":"Li","family":"HUANG","sequence":"first","affiliation":[{"name":"School of Management, Hefei University of Technology"},{"name":"School of Management Science and Engineering, Anhui University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"ZHENG","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Anhui University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai","family":"DING","sequence":"additional","affiliation":[{"name":"School of Management, Hefei University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhi","family":"LIU","sequence":"additional","affiliation":[{"name":"Department of Mathematical and Systems Engineering, Shizuoka University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"HUANG","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Anhui University of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"publisher","unstructured":"[1] C. Cobos, H. Mu\u00f1oz-Collazos, R. Urbano-Mu\u00f1oz, M. Mendozaab, E. Leonc, and E. Herrera-Viedmade, \u201cClustering of web search results based on the cuckoo search algorithm and Balanced Bayesian Information Criterion,\u201d Information Sciences, vol.281, no.2, pp.248-264, Oct. 2014. 10.1016\/j.ins.2014.05.047","DOI":"10.1016\/j.ins.2014.05.047"},{"key":"2","doi-asserted-by":"publisher","unstructured":"[2] L. Liu, H. Mu, and J. Yang, \u201cGeneric constraints handling techniques in constrained multi-criteria optimization and its application,\u201d European Journal of Operational Research, vol.244, no.2, pp.576-591, July 2015. 10.1016\/j.ejor.2015.01.051","DOI":"10.1016\/j.ejor.2015.01.051"},{"key":"3","doi-asserted-by":"publisher","unstructured":"[3] R. Ruiz and C. Maroto, \u201cA genetic algorithm for hybrid flowshops with sequence dependent setup times and machine eligibility,\u201d European Journal of Operational Research, vol.169, no.3, pp.781-800, 2006. 10.1016\/j.ejor.2004.06.038","DOI":"10.1016\/j.ejor.2004.06.038"},{"key":"4","doi-asserted-by":"publisher","unstructured":"[4] C. Kea, Z. Fengyua, and L. Alingb, \u201cChaotic Dynamic Weight Particle Swarm Optimization for Numerical Function Optimization,\u201d Knowledge-Based Systems, vol.139, no.3, pp.23-40, Jan. 2018. 10.1016\/j.knosys.2017.10.011","DOI":"10.1016\/j.knosys.2017.10.011"},{"key":"5","doi-asserted-by":"publisher","unstructured":"[5] W.-N. Chen, J. Zhang, Y. Lin, N. Chen, Z.-H. Zhan, H.S.-H. Chung, Y. Li, and Y.-H. Shi, \u201cParticle Swarm Optimization With an Aging Leader and Challengers,\u201d IEEE Trans. Evol. Comput., vol.17, no.2, pp.241-258, April 2013. 10.1109\/tevc.2011.2173577","DOI":"10.1109\/TEVC.2011.2173577"},{"key":"6","doi-asserted-by":"publisher","unstructured":"[6] W.H. Lim and N.A.M. Isa, \u201cBidirectional teaching and peer-learning particle swarm optimization,\u201dInformation Sciences, vol.280, no.4, pp.111-134, Oct. 2014. 10.1016\/j.ins.2014.04.050","DOI":"10.1016\/j.ins.2014.04.050"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] M. Nasirac, S. Das, D. Maity, S. Sengupta, U. Halder, and P.N. Suganthan, \u201cA dynamic neighborhood learning based particle swarm optimizer for global numerical optimization,\u201d Information Sciences, vol.209, no.5, pp.16-36, Nov. 2012. 10.1016\/j.ins.2012.04.028","DOI":"10.1016\/j.ins.2012.04.028"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[2] L. Liu, H. Mu, and J. Yang, \u201cGeneric constraints handling techniques in constrained multi-criteria optimization and its application,\u201d European Journal of Operational Research, vol.244, no.2, pp.576-591, July 2015. 10.1016\/j.ejor.2015.01.051","DOI":"10.1016\/j.ejor.2015.01.051"},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] X. Li, J. Wang, and M. Yin, \u201cEnhancing the performance of cuckoo search algorithm using orthogonal learning method,\u201d Neural Computing &amp; Applications, vol.24, no.6, pp.1233-1247, May 2014. 10.1007\/s00521-013-1354-6","DOI":"10.1007\/s00521-013-1354-6"},{"key":"10","doi-asserted-by":"publisher","unstructured":"[10] X. Li and M. Yin, \u201cModified cuckoo search algorithm with self adaptive parameter method,\u201d Information Sciences, vol.298, pp.80-97 March 2015. (DOI:10.1016\/j.ins.2014.11.042) 10.1016\/j.ins.2014.11.042","DOI":"10.1016\/j.ins.2014.11.042"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] L. Huang, S. Ding, S. Yu, J. Wang, and K. Lu \u201cChaos-enhanced Cuckoo search optimization algorithms for global optimization,\u201d Applied Mathematical Modelling, vol.40, no.5, pp.3860-3875, March 2016. 10.1016\/j.apm.2015.10.052","DOI":"10.1016\/j.apm.2015.10.052"},{"key":"12","doi-asserted-by":"publisher","unstructured":"[12] X. Liu and M. Fu, \u201cCuckoo search algorithm based on frog leaping local search and chaos theory,\u201d Applied Mathematics &amp; Computation, vol.266, pp.1083-1092, Sept. 2015. 10.1016\/j.amc.2015.06.041","DOI":"10.1016\/j.amc.2015.06.041"},{"key":"13","doi-asserted-by":"publisher","unstructured":"[13] D.H. Wolpert and W.G. Macready, \u201cNo free lunch theorems for optimization,\u201d IEEE Trans. Evol. Comput., vol.1, no.1, pp.67-82, April 1997. 10.1109\/4235.585893","DOI":"10.1109\/4235.585893"},{"key":"14","doi-asserted-by":"publisher","unstructured":"[14] Z. Zhao, J. Wang, J. Zhao, and Z. Su, \u201cUsing a Grey model optimized by Differential Evolution algorithm to forecast the per capita annual net income of rural households in China,\u201d Omega, vol.40, no.5, pp.525-532, Oct. 2012. 10.1016\/j.omega.2011.10.003","DOI":"10.1016\/j.omega.2011.10.003"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] M. Ali, P. Siarry, and M. Pant, \u201cAn efficient Differential Evolution based algorithm for solving multi-objective optimization problems,\u201d European Journal of Operational Research, vol.217 no.2, pp.404-416, March 2012. 10.1016\/j.ejor.2011.09.025","DOI":"10.1016\/j.ejor.2011.09.025"},{"key":"16","doi-asserted-by":"publisher","unstructured":"[16] A.W. Mohamed and P.N. Suganthan, \u201cReal-parameter unconstrained optimization based on enhanced fitness-adaptive differential evolution algorithm with novel mutation,\u201d Soft Computing, vol.22, no.10, pp.3215-3235, May 2018. 10.1007\/s00500-017-2777-2","DOI":"10.1007\/s00500-017-2777-2"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] X.S. Yang and S. Deb, \u201cCuckoo Search via L\u00e9vy Flight, \u201cProc. World Congress on Nature &amp; Biologically Inspired Computing, pp.210-214, IEEE, India, 2009. 10.1109\/nabic.2009.5393690","DOI":"10.1109\/NABIC.2009.5393690"},{"key":"18","doi-asserted-by":"publisher","unstructured":"[18] L.d.S. Coelho, T.C. Bora, and V.C. Mariani, \u201cDifferential evolution based on truncated L\u00e9vy-type flights a dispatch problems[J],\u201d Int. J. Electrical Power &amp; Energy Systems, vol.57, pp.178-188, May 2014. 10.1016\/j.ijepes.2013.11.024","DOI":"10.1016\/j.ijepes.2013.11.024"},{"key":"19","doi-asserted-by":"publisher","unstructured":"[19] W. Chu, X. Gao, and S. Sorooshian, \u201cHandling boundary constraints for particle swarm optimization in high-dimensional search space,\u201d Information Sciences, vol.181, no.20, pp.4569-4581, Oct. 2011. 10.1016\/j.ins.2010.11.030","DOI":"10.1016\/j.ins.2010.11.030"},{"key":"20","doi-asserted-by":"crossref","unstructured":"[20] N. Padhye, K. Deb, and P. Mittal, \u201cBoundary Handling Approaches in Particle Swarm Optimization,\u201d Proc. Seventh Int. Conf. Bio-Inspired Computing: Theories and Applications (BIC-TA 2012). Springer India, pp.287-298, 2013. 10.1007\/978-81-322-1038-2_25","DOI":"10.1007\/978-81-322-1038-2_25"},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] S. Helwig and R. Wanka, \u201cParticle Swarm Optimization in High-Dimensional Bounded Search Spaces,\u201d Proc. 2007 IEEE Swarm Intelligence Symposium, pp.198-205, 2007. 10.1109\/sis.2007.368046","DOI":"10.1109\/SIS.2007.368046"},{"key":"22","doi-asserted-by":"publisher","unstructured":"[22] J.J. Liang, A.K. Qin, P.N. Suganthan, and S. Baskar, \u201cComprehensive learning particle swarm optimizer for global optimization of multimodal functions,\u201d IEEE Trans. Evol. Comput., vol.10, no.3, pp.281-295, June 2006. 10.1109\/tevc.2005.857610","DOI":"10.1109\/TEVC.2005.857610"},{"key":"23","doi-asserted-by":"crossref","unstructured":"[23] J.J. Liang, A.K. Qin, P.N. Suganthan, and S. Baskar, \u201cEvaluation of Comprehensive Learning Particle Swarm Optimizer[C],\u201d Neural Information Processing, 11th International Conference, ICONIP 2004, Lecture Notes in Computer Science, pp.230-235, Calcutta, India, 2004. 10.1007\/978-3-540-30499-9_34","DOI":"10.1007\/978-3-540-30499-9_34"},{"key":"24","doi-asserted-by":"publisher","unstructured":"[24] W.H. Lim and N.A.M. Isa, \u201cAn adaptive two-layer particle swarm optimization with elitist learning strategy,\u201d Information Sciences, vol.273, no.3, pp.49-72, July 2014. 10.1016\/j.ins.2014.03.031","DOI":"10.1016\/j.ins.2014.03.031"},{"key":"25","unstructured":"[25] J.J. Liang, B.Y. Qu, and P.N. Suganthan, A.G. Hern\u00e1ndez-D\u00edaz \u201cProblem definitions and evaluation criteria for the cec 2013 special session on real-parameter optimization,\u201d Int. J. Computer Assisted Radiology Surgery, 2013."},{"key":"26","doi-asserted-by":"publisher","unstructured":"[26] S. Sun and J. Li, \u201cA two-swarm cooperative particle swarms optimization,\u201d Swarm &amp; Evolutionary Computation, vol.15, pp.1-18, April 2014. 10.1016\/j.swevo.2013.10.003","DOI":"10.1016\/j.swevo.2013.10.003"}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E102.D\/10\/E102.D_2019EDP7013\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,5]],"date-time":"2019-10-05T03:26:24Z","timestamp":1570245984000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E102.D\/10\/E102.D_2019EDP7013\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10,1]]},"references-count":26,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2019]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2019edp7013","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,10,1]]}}}