{"title":"一种改进粒子群优化算法的新方法","authors":"M. Qais, Zeyad AbdulWahid","doi":"10.1109/ICMSAO.2013.6552560","DOIUrl":null,"url":null,"abstract":"In this paper, we introduced some modifications in the standard particles swarm optimization algorithm to get better results. We modified the velocity equation by inserting triangular functions (cosine and sine), increasing inertia weight and introducing a new method to avoid the stagnation problem. The modified algorithm named as Triangular Particle Swarm Optimization (TriPSO) was tested by five well-known benchmark functions (Sphere, Ackley, Rastrigin, Rosenbrock and Schwefel p2.26). The obtained results are compared with those of standard PSO and different published improved PSO algorithms (SPSO, PSO-XD, CPSO-S and PSO-P5), the comparison showed that TriPSO has the best results.","PeriodicalId":339666,"journal":{"name":"2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A new method for improving particle swarm optimization algorithm (TriPSO)\",\"authors\":\"M. Qais, Zeyad AbdulWahid\",\"doi\":\"10.1109/ICMSAO.2013.6552560\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduced some modifications in the standard particles swarm optimization algorithm to get better results. We modified the velocity equation by inserting triangular functions (cosine and sine), increasing inertia weight and introducing a new method to avoid the stagnation problem. The modified algorithm named as Triangular Particle Swarm Optimization (TriPSO) was tested by five well-known benchmark functions (Sphere, Ackley, Rastrigin, Rosenbrock and Schwefel p2.26). The obtained results are compared with those of standard PSO and different published improved PSO algorithms (SPSO, PSO-XD, CPSO-S and PSO-P5), the comparison showed that TriPSO has the best results.\",\"PeriodicalId\":339666,\"journal\":{\"name\":\"2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMSAO.2013.6552560\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMSAO.2013.6552560","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new method for improving particle swarm optimization algorithm (TriPSO)
In this paper, we introduced some modifications in the standard particles swarm optimization algorithm to get better results. We modified the velocity equation by inserting triangular functions (cosine and sine), increasing inertia weight and introducing a new method to avoid the stagnation problem. The modified algorithm named as Triangular Particle Swarm Optimization (TriPSO) was tested by five well-known benchmark functions (Sphere, Ackley, Rastrigin, Rosenbrock and Schwefel p2.26). The obtained results are compared with those of standard PSO and different published improved PSO algorithms (SPSO, PSO-XD, CPSO-S and PSO-P5), the comparison showed that TriPSO has the best results.