{"title":"具有任务合并的EOS调度问题的模拟退火算法","authors":"G. Peng, Li Wen, Yao Feng, Bai Baocun, Yang Jing","doi":"10.1109/ICMIC.2011.5973764","DOIUrl":null,"url":null,"abstract":"The slew operations of earth observation satellites are tightly constrained, observation scheduling with task merging can improve satellites observing efficiency. The model of satellite observation scheduling problem with task merging is proposed in this paper article and a Very Fast Simulated Annealing algorithm (VFSA) is developed to solve the problem. The VFSA algorithm employs compose and decompose neighborhoods for dynamic task merging. To avoid the local optimum solutions and improve the exploration abilities, re-annealing and three diversification strategies, perturb, rearrange and restart are defined in VFSA. Experiments results show the effectiveness of our approach.","PeriodicalId":210380,"journal":{"name":"Proceedings of 2011 International Conference on Modelling, Identification and Control","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2011-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Simulated annealing algorithm for EOS scheduling problem with task merging\",\"authors\":\"G. Peng, Li Wen, Yao Feng, Bai Baocun, Yang Jing\",\"doi\":\"10.1109/ICMIC.2011.5973764\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The slew operations of earth observation satellites are tightly constrained, observation scheduling with task merging can improve satellites observing efficiency. The model of satellite observation scheduling problem with task merging is proposed in this paper article and a Very Fast Simulated Annealing algorithm (VFSA) is developed to solve the problem. The VFSA algorithm employs compose and decompose neighborhoods for dynamic task merging. To avoid the local optimum solutions and improve the exploration abilities, re-annealing and three diversification strategies, perturb, rearrange and restart are defined in VFSA. Experiments results show the effectiveness of our approach.\",\"PeriodicalId\":210380,\"journal\":{\"name\":\"Proceedings of 2011 International Conference on Modelling, Identification and Control\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2011 International Conference on Modelling, Identification and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMIC.2011.5973764\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2011 International Conference on Modelling, Identification and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMIC.2011.5973764","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Simulated annealing algorithm for EOS scheduling problem with task merging
The slew operations of earth observation satellites are tightly constrained, observation scheduling with task merging can improve satellites observing efficiency. The model of satellite observation scheduling problem with task merging is proposed in this paper article and a Very Fast Simulated Annealing algorithm (VFSA) is developed to solve the problem. The VFSA algorithm employs compose and decompose neighborhoods for dynamic task merging. To avoid the local optimum solutions and improve the exploration abilities, re-annealing and three diversification strategies, perturb, rearrange and restart are defined in VFSA. Experiments results show the effectiveness of our approach.
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