{"title":"Optimization Design of Ammunition Scheduling Scheme for Carrier-based Aircraft based on Improved DPSO Algorithm","authors":"Liting Wang, Fuqiang Li, Jing-lian Huang, Xiao-Na Zheng","doi":"10.1145/3579654.3579691","DOIUrl":null,"url":null,"abstract":"Abstract: In order to minimize the execution time of ammunition scheduling scheme, an ammunition scheduling model for carrier-based aircraft is established in this paper, and a improved discrete particle swarm optimization (IDPSO) algorithm is designed for multiple links, multiple ammunition points and multiple demand points in the ammunition scheduling process. The IDPSO algorithm overcomes the disadvantage that the basic particle swarm is hard to deal with the discrete problem, by discretizing the particle speed and coordinates. The simulation results show that the IDPSO algorithm has faster convergence speed and global optimization ability. At the same time, the applicability of the scheduling model and the effectiveness of the IDPSO algorithm are verified. CCS CONCEPTS • Computing methodologies • Modeling and simulation • Model development and analysis","PeriodicalId":146783,"journal":{"name":"Proceedings of the 2022 5th International Conference on Algorithms, Computing and Artificial Intelligence","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2022 5th International Conference on Algorithms, Computing and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3579654.3579691","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract: In order to minimize the execution time of ammunition scheduling scheme, an ammunition scheduling model for carrier-based aircraft is established in this paper, and a improved discrete particle swarm optimization (IDPSO) algorithm is designed for multiple links, multiple ammunition points and multiple demand points in the ammunition scheduling process. The IDPSO algorithm overcomes the disadvantage that the basic particle swarm is hard to deal with the discrete problem, by discretizing the particle speed and coordinates. The simulation results show that the IDPSO algorithm has faster convergence speed and global optimization ability. At the same time, the applicability of the scheduling model and the effectiveness of the IDPSO algorithm are verified. CCS CONCEPTS • Computing methodologies • Modeling and simulation • Model development and analysis