{"title":"具有确定性和离散动力学的基于种群的优化","authors":"Yuya Kurita, T. Tsubone","doi":"10.1109/CEC.2015.7257216","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a method celled Integer algorithm of Population-based Optimization based on Piecewise Constant Oscillator (IPO-PCO). Well known Particle Swarm Optimization method (PSO) has several open problems. We focus on two of them. First, in order to solve discrete optimization problems, PSO needs some modifications. Second, since PSO has stochastic factors in the dynamics, the analysis of the dynamic behavior is pretty complex. Some means to resolve the problems have been proposed in previous works. However there is no method which can manage both problems. Then, this paper considers a deterministic and discrete method. We compare the proposed method with a discretized PSO by repositioned to near lattice point and verify the effectiveness of the propose method.","PeriodicalId":403666,"journal":{"name":"2015 IEEE Congress on Evolutionary Computation (CEC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Population-based optimization having deterministic and discrete dynamics\",\"authors\":\"Yuya Kurita, T. Tsubone\",\"doi\":\"10.1109/CEC.2015.7257216\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a method celled Integer algorithm of Population-based Optimization based on Piecewise Constant Oscillator (IPO-PCO). Well known Particle Swarm Optimization method (PSO) has several open problems. We focus on two of them. First, in order to solve discrete optimization problems, PSO needs some modifications. Second, since PSO has stochastic factors in the dynamics, the analysis of the dynamic behavior is pretty complex. Some means to resolve the problems have been proposed in previous works. However there is no method which can manage both problems. Then, this paper considers a deterministic and discrete method. We compare the proposed method with a discretized PSO by repositioned to near lattice point and verify the effectiveness of the propose method.\",\"PeriodicalId\":403666,\"journal\":{\"name\":\"2015 IEEE Congress on Evolutionary Computation (CEC)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Congress on Evolutionary Computation (CEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CEC.2015.7257216\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Congress on Evolutionary Computation (CEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEC.2015.7257216","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Population-based optimization having deterministic and discrete dynamics
In this paper, we propose a method celled Integer algorithm of Population-based Optimization based on Piecewise Constant Oscillator (IPO-PCO). Well known Particle Swarm Optimization method (PSO) has several open problems. We focus on two of them. First, in order to solve discrete optimization problems, PSO needs some modifications. Second, since PSO has stochastic factors in the dynamics, the analysis of the dynamic behavior is pretty complex. Some means to resolve the problems have been proposed in previous works. However there is no method which can manage both problems. Then, this paper considers a deterministic and discrete method. We compare the proposed method with a discretized PSO by repositioned to near lattice point and verify the effectiveness of the propose method.