{"title":"Non-Swarm Plant Intelligence Algorithm: BladderWorts Suction (BWS) Algorithm","authors":"R. Gowri, R. Rathipriya","doi":"10.1109/ICCSDET.2018.8821225","DOIUrl":null,"url":null,"abstract":"BladderWorts Suction (BWS) Algorithm is proposed in this article, which is a novel Plant intelligence inspired meta-heuristic non-swarm algorithm. The concept of non-swarm intelligence is focused in this paper because of the autonomous behavior of the individuals. In the swarm intelligence algorithms, the individuals are influenced by the global knowledge. Sometimes, the small change by an individual may result in group level behavior. The core inspiration for this non-swarm optimization algorithm is the foraging suction mechanism of the aquatic plant Utricularia (Bladderworts). The worst bladders are regenerated periodically to accelerate the solution search of the stagnant bladders at local optima. It is tested with different benchmark test functions. The optimizing tendency of this algorithm is studied empirically, which yields good results. Comparatively, BWS algorithm also produces positive insights like various other popular optimization techniques.","PeriodicalId":157362,"journal":{"name":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSDET.2018.8821225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
BladderWorts Suction (BWS) Algorithm is proposed in this article, which is a novel Plant intelligence inspired meta-heuristic non-swarm algorithm. The concept of non-swarm intelligence is focused in this paper because of the autonomous behavior of the individuals. In the swarm intelligence algorithms, the individuals are influenced by the global knowledge. Sometimes, the small change by an individual may result in group level behavior. The core inspiration for this non-swarm optimization algorithm is the foraging suction mechanism of the aquatic plant Utricularia (Bladderworts). The worst bladders are regenerated periodically to accelerate the solution search of the stagnant bladders at local optima. It is tested with different benchmark test functions. The optimizing tendency of this algorithm is studied empirically, which yields good results. Comparatively, BWS algorithm also produces positive insights like various other popular optimization techniques.