{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T02:15:53Z","timestamp":1792030553975,"version":"4.4.0"},"reference-count":43,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"university scientific research projects","award":["2024AH051989"],"award-info":[{"award-number":["2024AH051989"]}]},{"name":"university scientific research projects","award":["2022AH051674"],"award-info":[{"award-number":["2022AH051674"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biomimetics"],"abstract":"<jats:p>This work presents a rat optimization algorithm (ROA), which simulates the social behavior of rats and is a new nature-inspired optimization technique. The ROA consists of three operators that simulate rats searching for prey, chasing and fighting prey, and jumping and hunting prey to deal with optimization issues. The Levy flight strategy is introduced into the ROA to keep the algorithm from running into issues with slow convergence and local optimums. The ROA is tested with four real-world engineering optimization issues and twenty-two benchmark functions. Experiments show that the ROA is particularly effective at solving real-world optimization problems compared to other well-known optimization techniques.<\/jats:p>","DOI":"10.3390\/biomimetics9120732","type":"journal-article","created":{"date-parts":[[2024,12,3]],"date-time":"2024-12-03T11:48:56Z","timestamp":1733226536000},"page":"732","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Nature-Inspired Approach: A Novel Rat Optimization Algorithm for Global Optimization"],"prefix":"10.3390","volume":"9","author":[{"given":"Pianpian","family":"Yan","sequence":"first","affiliation":[{"name":"School of Electrical and Photoelectronic Engineering, West Anhui University, Lu\u2019an 237012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5988-702X","authenticated-orcid":false,"given":"Jinzhong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical and Photoelectronic Engineering, West Anhui University, Lu\u2019an 237012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tan","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical and Photoelectronic Engineering, West Anhui University, Lu\u2019an 237012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cor.2014.10.008","article-title":"Water wave optimization: A new nature-inspired metaheuristic","volume":"55","author":"Zheng","year":"2015","journal-title":"Comput. 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