{"title":"Linear Antenna Array Synthesis with Invasive Weed Optimization Algorithm","authors":"S. Pal, Aniruddha Basak, Swagatam Das, A. Abraham","doi":"10.1109/SoCPaR.2009.42","DOIUrl":null,"url":null,"abstract":"Linear antenna array design is one of the most important electromagnetic optimization problems of current interest. This article describes the application of a recently developed metaheuristic algorithm, known as the Invasive Weed Optimization (IWO), to optimize the spacing between the elements of the linear array to produce a radiation pattern with minimum side lobe level and null placement control. The results of the IWO algorithm have been shown to meet or beat the results obtained using other state-of-the-art metaheuristics like the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Memetic Algorithms (MA), and Tabu Search (TS) in a statistically meaningful way","PeriodicalId":284743,"journal":{"name":"2009 International Conference of Soft Computing and Pattern Recognition","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"47","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference of Soft Computing and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SoCPaR.2009.42","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 47
Abstract
Linear antenna array design is one of the most important electromagnetic optimization problems of current interest. This article describes the application of a recently developed metaheuristic algorithm, known as the Invasive Weed Optimization (IWO), to optimize the spacing between the elements of the linear array to produce a radiation pattern with minimum side lobe level and null placement control. The results of the IWO algorithm have been shown to meet or beat the results obtained using other state-of-the-art metaheuristics like the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Memetic Algorithms (MA), and Tabu Search (TS) in a statistically meaningful way