{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T21:42:14Z","timestamp":1769636534358,"version":"3.49.0"},"reference-count":30,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T00:00:00Z","timestamp":1635465600000},"content-version":"vor","delay-in-days":301,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61763019"],"award-info":[{"award-number":["61763019"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61364025"],"award-info":[{"award-number":["61364025"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62041603"],"award-info":[{"award-number":["62041603"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004479","name":"Natural Science Foundation of Jiangxi Province","doi-asserted-by":"publisher","award":["20202BABL202036"],"award-info":[{"award-number":["20202BABL202036"]}],"id":[{"id":"10.13039\/501100004479","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004479","name":"Natural Science Foundation of Jiangxi Province","doi-asserted-by":"publisher","award":["20202BABL202019"],"award-info":[{"award-number":["20202BABL202019"]}],"id":[{"id":"10.13039\/501100004479","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>Differential evolution (DE) is a robust algorithm of global optimization which has been used for solving many of the real\u2010world applications since it was proposed. However, binomial crossover does not allow for a sufficiently effective search in local space. DE\u2019s local search performance is therefore relatively poor. In particular, DE is applied to solve the complex optimization problem. In this case, inefficiency in local research seriously limits its overall performance. To overcome this disadvantage, this paper introduces a new local search scheme based on Hadamard matrix (HLS). The HLS improves the probability of finding the optimal solution through producing multiple offspring in the local space built by the target individual and its descendants. The HLS has been implemented in four classical DE algorithms and jDE, a variant of DE. The experiments are carried out on a set of widely used benchmark functions. For 20 benchmark problems, the four DE schemes using HLS have better results than the corresponding DE schemes, accounting for 80%, 75%, 65%, and 65% respectively. Also, the performance of jDE with HLS is better than that of jDE on 50% test problems. The experimental results and statistical analysis have revealed that HLS could effectively improve the overall performance of DE and jDE.<\/jats:p>","DOI":"10.1155\/2021\/8930980","type":"journal-article","created":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T22:05:08Z","timestamp":1635545108000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Enhanced Differential Evolution Algorithm with Local Search Based on Hadamard Matrix"],"prefix":"10.1155","volume":"2021","author":[{"given":"Changshou","family":"Deng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2300-5563","authenticated-orcid":false,"given":"Xiaogang","family":"Dong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yucheng","family":"Tan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hu","family":"Peng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,10,29]]},"reference":[{"key":"e_1_2_10_1_2","doi-asserted-by":"publisher","DOI":"10.1023\/a:1008202821328"},{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/access.2018.2793298"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2018.01.029"},{"key":"e_1_2_10_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10845-016-1199-9"},{"key":"e_1_2_10_5_2","doi-asserted-by":"publisher","DOI":"10.4304\/jcp.9.8.1922-1927"},{"key":"e_1_2_10_6_2","doi-asserted-by":"crossref","unstructured":"DesaiC. K.andShaikhA. A. Drill wear monitoring using artificial neural network with differential evolution learning Proceedings of the IEEE International Conference on Industrial Technology December 2006 Mumbai India 2019\u20132022 https:\/\/doi.org\/10.1109\/icit.2006.372500 2-s2.0-51349148090.","DOI":"10.1109\/ICIT.2006.372500"},{"key":"e_1_2_10_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijnonlinmec.2019.103288"},{"key":"e_1_2_10_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMAG.2020.3032892"},{"key":"e_1_2_10_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2018.06.010"},{"key":"e_1_2_10_10_2","doi-asserted-by":"publisher","DOI":"10.22266\/ijies2016.1231.06"},{"key":"e_1_2_10_11_2","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/7974218"},{"key":"e_1_2_10_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/tcyb.2013.2239988"},{"key":"e_1_2_10_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2017.07.010"},{"key":"e_1_2_10_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/tevc.2006.872133"},{"key":"e_1_2_10_15_2","doi-asserted-by":"publisher","DOI":"10.1109\/tevc.2008.927706"},{"key":"e_1_2_10_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2012.09.019"},{"key":"e_1_2_10_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2011.09.001"},{"key":"e_1_2_10_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2007.894200"},{"key":"e_1_2_10_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2004.06.009"},{"key":"e_1_2_10_20_2","doi-asserted-by":"publisher","DOI":"10.1049\/cje.2016.11.010"},{"key":"e_1_2_10_21_2","doi-asserted-by":"crossref","unstructured":"NomanN.andIbaH. Enhancing differential evolution performance with local search for high dimensional function optimization Proceedings of the 7th Annual Conference on Genetic and Evolutionary Computation June 2005 New York NY USA 967\u2013974 https:\/\/doi.org\/10.1145\/1068009.1068174 2-s2.0-32444442367.","DOI":"10.1145\/1068009.1068174"},{"key":"e_1_2_10_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/tevc.2007.895272"},{"key":"e_1_2_10_23_2","doi-asserted-by":"crossref","unstructured":"AliM. PantM. andNagarA. Two local search strategies for Differential Evolution Proceedings of the IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications IEEE May 2010 Changsha China 1429\u20131435 https:\/\/doi.org\/10.1109\/bicta.2010.5645285 2-s2.0-78650627005.","DOI":"10.1109\/BICTA.2010.5645285"},{"key":"e_1_2_10_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eij.2014.07.001"},{"key":"e_1_2_10_25_2","doi-asserted-by":"crossref","unstructured":"NomanN. BollegalaD. andIbaH. Differential evolution with self-adaptive local search Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation July 2011 Dublin Ireland 1099\u20131106 https:\/\/doi.org\/10.1145\/2001576.2001725 2-s2.0-84860415000.","DOI":"10.1145\/2001576.2001725"},{"key":"e_1_2_10_26_2","doi-asserted-by":"crossref","unstructured":"OrtizM. L.andXiongN. Using random local search helps in avoiding local optimum in differential evolution Proceedings of the IASTED International Conference on Artificial Intelligence and Applications 2014 Innsbruck Austria 816\u2013021 https:\/\/doi.org\/10.2316\/p.2014.816-021 2-s2.0-84898444101.","DOI":"10.2316\/P.2014.816-021"},{"key":"e_1_2_10_27_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-014-1482-7"},{"key":"e_1_2_10_28_2","doi-asserted-by":"publisher","DOI":"10.1090\/S0002-9939-1962-0142557-0"},{"key":"e_1_2_10_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/4235.771163"},{"key":"e_1_2_10_30_2","doi-asserted-by":"crossref","unstructured":"WangH. WuZ. andLiuY. Space transformation search: a new evolutionary technique Proceedings of the 1st ACM\/SIGEVO Summit on Genetic and Evolutionary Computation May 2009 Shanghai China 537\u2013544.","DOI":"10.1145\/1543834.1543907"}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2021\/8930980.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2021\/8930980.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2021\/8930980","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T11:52:12Z","timestamp":1722945132000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2021\/8930980"}},"subtitle":[],"editor":[{"given":"Mario","family":"Versaci","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":30,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1155\/2021\/8930980"],"URL":"https:\/\/doi.org\/10.1155\/2021\/8930980","archive":["Portico"],"relation":{},"ISSN":["1687-5265","1687-5273"],"issn-type":[{"value":"1687-5265","type":"print"},{"value":"1687-5273","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"2021-08-12","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-09-17","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-10-29","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"8930980"}}