Michal Pluhacek, T. Kadavy, Anezka Kazikova, Adam Viktorin, R. Šenkeřík
{"title":"用复杂网络分析解释粒子群优化的内部动力学","authors":"Michal Pluhacek, T. Kadavy, Anezka Kazikova, Adam Viktorin, R. Šenkeřík","doi":"10.1109/COMPENG50184.2022.9905435","DOIUrl":null,"url":null,"abstract":"In this paper, we present the relation between the inner dynamics of the particle swarm optimization algorithm and the properties of a complex network recording the information transfer in the population. Using population diversity as an example, we argue that the complex network analysis is a viable tool for assessing the state of the population and the eventual necessity of an adaptive intervention.","PeriodicalId":211056,"journal":{"name":"2022 IEEE Workshop on Complexity in Engineering (COMPENG)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Inner Dynamics of Particle Swarm Optimization Interpreted by Complex Network Analysis\",\"authors\":\"Michal Pluhacek, T. Kadavy, Anezka Kazikova, Adam Viktorin, R. Šenkeřík\",\"doi\":\"10.1109/COMPENG50184.2022.9905435\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present the relation between the inner dynamics of the particle swarm optimization algorithm and the properties of a complex network recording the information transfer in the population. Using population diversity as an example, we argue that the complex network analysis is a viable tool for assessing the state of the population and the eventual necessity of an adaptive intervention.\",\"PeriodicalId\":211056,\"journal\":{\"name\":\"2022 IEEE Workshop on Complexity in Engineering (COMPENG)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Workshop on Complexity in Engineering (COMPENG)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPENG50184.2022.9905435\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Workshop on Complexity in Engineering (COMPENG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPENG50184.2022.9905435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Inner Dynamics of Particle Swarm Optimization Interpreted by Complex Network Analysis
In this paper, we present the relation between the inner dynamics of the particle swarm optimization algorithm and the properties of a complex network recording the information transfer in the population. Using population diversity as an example, we argue that the complex network analysis is a viable tool for assessing the state of the population and the eventual necessity of an adaptive intervention.