{"title":"用培养粒子群算法求解武器目标分配问题","authors":"Shaolei Wang, Weiyi Chen","doi":"10.1109/IHMSC.2012.41","DOIUrl":null,"url":null,"abstract":"The weapon-target assignment is a very complicated problem and a key point in the warship formations' air defense operation. In this paper, a cultural particle swarm optimization algorithm for solving WTA problems is proposed. The general idea of the proposed algorithm is to combine the advantages of PSO which integrates local search and global search scheme possesses high search efficiency, and that of cultural algorithm which combines the search method with the knowledge representation scheme for collecting and reasoning knowledge about individual experience to avoid premature convergence. An example is used to verify the correctness and effectiveness of the proposed cultural PSO algorithm, comparing with both the traditional PSO method and the genetic algorithm method. The simulation results demonstrate that the proposed algorithm has rapid convergence speed and higher solution precision.","PeriodicalId":431532,"journal":{"name":"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Solving Weapon-Target Assignment Problems by Cultural Particle Swarm Optimization\",\"authors\":\"Shaolei Wang, Weiyi Chen\",\"doi\":\"10.1109/IHMSC.2012.41\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The weapon-target assignment is a very complicated problem and a key point in the warship formations' air defense operation. In this paper, a cultural particle swarm optimization algorithm for solving WTA problems is proposed. The general idea of the proposed algorithm is to combine the advantages of PSO which integrates local search and global search scheme possesses high search efficiency, and that of cultural algorithm which combines the search method with the knowledge representation scheme for collecting and reasoning knowledge about individual experience to avoid premature convergence. An example is used to verify the correctness and effectiveness of the proposed cultural PSO algorithm, comparing with both the traditional PSO method and the genetic algorithm method. The simulation results demonstrate that the proposed algorithm has rapid convergence speed and higher solution precision.\",\"PeriodicalId\":431532,\"journal\":{\"name\":\"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IHMSC.2012.41\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 4th International Conference on Intelligent Human-Machine Systems and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHMSC.2012.41","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Solving Weapon-Target Assignment Problems by Cultural Particle Swarm Optimization
The weapon-target assignment is a very complicated problem and a key point in the warship formations' air defense operation. In this paper, a cultural particle swarm optimization algorithm for solving WTA problems is proposed. The general idea of the proposed algorithm is to combine the advantages of PSO which integrates local search and global search scheme possesses high search efficiency, and that of cultural algorithm which combines the search method with the knowledge representation scheme for collecting and reasoning knowledge about individual experience to avoid premature convergence. An example is used to verify the correctness and effectiveness of the proposed cultural PSO algorithm, comparing with both the traditional PSO method and the genetic algorithm method. The simulation results demonstrate that the proposed algorithm has rapid convergence speed and higher solution precision.