{"title":"一种基于正则跃迁发射计数向量的可达性图构建算法","authors":"G. Chiola, R. Carvajal-Schiaffino","doi":"10.1109/PNPM.2001.953361","DOIUrl":null,"url":null,"abstract":"The construction of the reachability graph presents the problem that its size may grow exponentially with respect to the size of the Petri-net model. For this reason, all available tools suffer restrictions due to the limitation of the available computational resources. We present a new, efficient algorithm based on a data structure that encodes canonical firing count vectors starting from the initial marking rather than token distributions. Our new algorithm applies to bounded and consistent Petri-net models. We define the main concept for this new marking representation, then we present performance results in terms of comparisons of space and time resources against the standard GreatSPN (Great Stochastic Petri Nets) solver.","PeriodicalId":364695,"journal":{"name":"Proceedings 9th International Workshop on Petri Nets and Performance Models","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2001-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A reachability graph construction algorithm based on canonical transition firing count vectors\",\"authors\":\"G. Chiola, R. Carvajal-Schiaffino\",\"doi\":\"10.1109/PNPM.2001.953361\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The construction of the reachability graph presents the problem that its size may grow exponentially with respect to the size of the Petri-net model. For this reason, all available tools suffer restrictions due to the limitation of the available computational resources. We present a new, efficient algorithm based on a data structure that encodes canonical firing count vectors starting from the initial marking rather than token distributions. Our new algorithm applies to bounded and consistent Petri-net models. We define the main concept for this new marking representation, then we present performance results in terms of comparisons of space and time resources against the standard GreatSPN (Great Stochastic Petri Nets) solver.\",\"PeriodicalId\":364695,\"journal\":{\"name\":\"Proceedings 9th International Workshop on Petri Nets and Performance Models\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 9th International Workshop on Petri Nets and Performance Models\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PNPM.2001.953361\",\"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 9th International Workshop on Petri Nets and Performance Models","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PNPM.2001.953361","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A reachability graph construction algorithm based on canonical transition firing count vectors
The construction of the reachability graph presents the problem that its size may grow exponentially with respect to the size of the Petri-net model. For this reason, all available tools suffer restrictions due to the limitation of the available computational resources. We present a new, efficient algorithm based on a data structure that encodes canonical firing count vectors starting from the initial marking rather than token distributions. Our new algorithm applies to bounded and consistent Petri-net models. We define the main concept for this new marking representation, then we present performance results in terms of comparisons of space and time resources against the standard GreatSPN (Great Stochastic Petri Nets) solver.