{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:35:10Z","timestamp":1760150110232,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,10,14]],"date-time":"2023-10-14T00:00:00Z","timestamp":1697241600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"King Saud University, Riyadh, Saudi Arabia","award":["RSPD2023R890"],"award-info":[{"award-number":["RSPD2023R890"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Symmetry in a differential evolution (DE) transforms a solution without impacting the family of solutions. For symmetrical problems in differential equations, DE is a strong evolutionary algorithm that provides a powerful solution to resolve global optimization problems. DE\/best\/1 and DE\/rand\/1 are the two most commonly used mutation strategies in DE. The former provides better exploitation while the latter ensures better exploration. DE\/Neighbor\/1 is an improved form of DE\/rand\/1 to maintain a balance between exploration and exploitation which was used with a random neighbor-based differential evolution (RNDE) algorithm. However, this mutation strategy slows down convergence. It should achieve a global minimum by using 1000 \u00d7 D, where D is the dimension, but due to exploration and exploitation balancing trade-offs, it can not achieve a global minimum within the range of 1000 \u00d7 D in some of the objective functions. To overcome this issue, a new and enhanced mutation strategy and algorithm have been introduced in this paper, called DE\/Neighbor\/2, as well as an improved random neighbor-based differential evolution algorithm. The new DE\/Neighbor\/2 mutation strategy also uses neighbor information such as DE\/Neighbor\/1; however, in addition, we add weighted differences after various tests. The DE\/Neighbor\/2 and IRNDE algorithm has also been tested on the same 27 commonly used benchmark functions on which the DE\/Neighbor\/1 mutation strategy and RNDE were tested. Experimental results demonstrate that the DE\/Neighbor\/2 mutation strategy and IRNDE algorithm show overall better and faster convergence than the DE\/Neighbor\/1 mutation strategy and RNDE algorithm. The parametric significance test shows that there is a significance difference in the performance of RNDE and IRNDE algorithms at the 0.05 level of significance.<\/jats:p>","DOI":"10.3390\/sym15101916","type":"journal-article","created":{"date-parts":[[2023,10,14]],"date-time":"2023-10-14T14:38:42Z","timestamp":1697294322000},"page":"1916","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Differential Evolution Using Enhanced Mutation Strategy Based on Random Neighbor Selection"],"prefix":"10.3390","volume":"15","author":[{"given":"Muhammad Hassan","family":"Baig","sequence":"first","affiliation":[{"name":"Department of Computer Science, Faculty of Computing and Information Technology, International Islamic University Islamabad, Islamabad 44000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4576-8585","authenticated-orcid":false,"given":"Qamar","family":"Abbas","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Computing and Information Technology, International Islamic University Islamabad, Islamabad 44000, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jamil","family":"Ahmad","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Hazara University, Mansehra 21120, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6067-382X","authenticated-orcid":false,"given":"Khalid","family":"Mahmood","sequence":"additional","affiliation":[{"name":"Institute of Computing and Information Technology, Gomal University, Dera Ismail Khan 29220, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1268-9613","authenticated-orcid":false,"given":"Sultan","family":"Alfarhood","sequence":"additional","affiliation":[{"name":"Department of Computer Science, College of Computer and Information Sciences, King Saud University, P.O. Box 51178, Riyadh 11543, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7445-7121","authenticated-orcid":false,"given":"Mejdl","family":"Safran","sequence":"additional","affiliation":[{"name":"Department of Computer Science, College of Computer and Information Sciences, King Saud University, P.O. Box 51178, Riyadh 11543, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8271-6496","authenticated-orcid":false,"given":"Imran","family":"Ashraf","sequence":"additional","affiliation":[{"name":"Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1023\/A:1008202821328","article-title":"Differential evolution\u2013A simple and efficient heuristic for global optimization over continuous spaces","volume":"11","author":"Storn","year":"1997","journal-title":"J. Glob. 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