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Compared with other algorithms, RSA is competitive but still suffers from low population diversity, unbalanced exploitation and exploration, and the tendency to fall into local optima. To overcome these shortcomings, a modified variant of RSA, named MRSA, is proposed in this paper. First, an adaptive chaotic reverse learning strategy is employed to enhance the population diversity. Second, an elite alternative pooling strategy is proposed to balance exploitation and exploration. Finally, a shifted distribution estimation strategy is used to correct the evolutionary direction and improve the algorithm performance. Subsequently, the superiority of MRSA is verified using 23 benchmark functions, IEEE CEC2017 benchmark functions, and robot path planning problems. The Friedman test, the Wilcoxon signed-rank test, and simulation results show that the proposed MRSA outperforms other comparative algorithms in terms of convergence accuracy, convergence speed, and stability.<\/jats:p>","DOI":"10.1155\/2022\/9752003","type":"journal-article","created":{"date-parts":[[2022,10,11]],"date-time":"2022-10-11T00:50:12Z","timestamp":1665449412000},"page":"1-20","source":"Crossref","is-referenced-by-count":20,"title":["A Modified Reptile Search Algorithm for Numerical Optimization Problems"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1291-0701","authenticated-orcid":true,"given":"Qihang","family":"Yuan","sequence":"first","affiliation":[{"name":"Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4602-1563","authenticated-orcid":true,"given":"Yongde","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, China"},{"name":"Foshan Baikang Robot Technology Co., Ltd, Nanhai, Foshan, Guangdong 528225, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9004-0174","authenticated-orcid":true,"given":"Xuesong","family":"Dai","sequence":"additional","affiliation":[{"name":"Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, Harbin University of Science and Technology, Harbin 150080, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Foshan Baikang Robot Technology Co., Ltd, Nanhai, Foshan, Guangdong 528225, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.inffus.2018.08.002","article-title":"An intelligent system for spam detection and identification of the most relevant features based on evolutionary random weight networks","volume":"48","author":"H. 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