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{"title":"基于分段对数拟合的蚁狮优化器","authors":"Cheng-ze Li, Geng-song Li, Yi Liu, Qi-bin Zheng","doi":"10.1002/tee.24275","DOIUrl":null,"url":null,"abstract":"<p>The ant lion optimizer (ALO) can address optimization problems by searching for approximate solutions. However, current implementations of ALO are prone to becoming trapped in local optima and exhibit mediocre random search capabilities. To address these issues, this paper introduces the piecewise logarithmic fitting-based ant lion optimizer (PLFALO). PLFALO initializes the population with Logistic mapping to increase the population diversity, then refines the original contraction of the ants' random walk boundary into a smoother process thereby enhancing random search capability, and finally mutates the ant position with a golden sine strategy to ensure the diversity of solutions. Exhaustive experiments have been conducted using six classic benchmark functions, comparing PLFALO against six state-of-the-art algorithms. The results confirm the superior performance of PLFALO. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.</p>","PeriodicalId":13435,"journal":{"name":"IEEJ Transactions on Electrical and Electronic Engineering","volume":"20 8","pages":"1294-1297"},"PeriodicalIF":1.1000,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Piecewise Logarithmic Fitting-Based Ant Lion Optimizer\",\"authors\":\"Cheng-ze Li, Geng-song Li, Yi Liu, Qi-bin Zheng\",\"doi\":\"10.1002/tee.24275\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The ant lion optimizer (ALO) can address optimization problems by searching for approximate solutions. However, current implementations of ALO are prone to becoming trapped in local optima and exhibit mediocre random search capabilities. To address these issues, this paper introduces the piecewise logarithmic fitting-based ant lion optimizer (PLFALO). PLFALO initializes the population with Logistic mapping to increase the population diversity, then refines the original contraction of the ants' random walk boundary into a smoother process thereby enhancing random search capability, and finally mutates the ant position with a golden sine strategy to ensure the diversity of solutions. Exhaustive experiments have been conducted using six classic benchmark functions, comparing PLFALO against six state-of-the-art algorithms. The results confirm the superior performance of PLFALO. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.</p>\",\"PeriodicalId\":13435,\"journal\":{\"name\":\"IEEJ Transactions on Electrical and Electronic Engineering\",\"volume\":\"20 8\",\"pages\":\"1294-1297\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2025-01-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEJ Transactions on Electrical and Electronic Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/tee.24275\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEJ Transactions on Electrical and Electronic Engineering","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/tee.24275","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
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