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However, the original KSO exhibits insufficient accuracy in local search, and there is a high probability that it may fail to achieve local optimization in complex tasks. Therefore, this paper proposes a multi-strategy enhanced KSO (MSKSO) to enhance the local search ability of the KSO. The MSKSO combines several control strategies, including chaotic initialization, chaotic local search mechanisms, the high-altitude walk strategy (HWS), and the Levy flight (LF), to effectively balance exploration and exploitation. The MSKSO is compared with ten well-known algorithms on 50 benchmark test functions to validate its performance, including single-peak, multi-peak, separable variable, and non-separable variable functions. Additionally, the MSKSO is applied to two real engineering economic emission dispatch (EED) problems in power systems. Experimental results demonstrate that the performance of the MSKSO nearly optimizes that of other well-known algorithms and achieves favorable results on the EED problem. These case studies verify that the MSKSO outperforms other algorithms and can serve as an effective optimization tool.<\/jats:p>","DOI":"10.1093\/jcde\/qwad110","type":"journal-article","created":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T07:21:50Z","timestamp":1702970510000},"page":"135-172","source":"Crossref","is-referenced-by-count":10,"title":["Multi-strategy enhanced kernel search optimization and its application in economic emission dispatch problems"],"prefix":"10.1093","volume":"11","author":[{"given":"Ruyi","family":"Dong","sequence":"first","affiliation":[{"name":"College of Information and Control Engineering, Jilin Institute of Chemical Technology , 132022 Jilin , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanan","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Information and Control Engineering, Jilin Institute of Chemical Technology , 132022 Jilin , 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