{"title":"基于萤火虫的业务流程优化","authors":"I. Salomie, V. Chifu, C. Pop, R. Suciu","doi":"10.1109/ICCP.2012.6356160","DOIUrl":null,"url":null,"abstract":"This paper presents a firefly-based method for business process optimization. Each artificial firefly has a candidate business process associated which is modeled as a causal matrix. The evolution of a candidate business process is achieved using genetic operators which aim to perform structural and resource allocation modifications. To establish whether a candidate business process is optimal, the cost and the execution time of the process are evaluated using a penalty-based fitness function. The firefly-based method has been evaluated on a set of generic scenarios and its performance has been analyzed using the fitness graph evolutionary measure.","PeriodicalId":406461,"journal":{"name":"2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Firefly-based business process optimization\",\"authors\":\"I. Salomie, V. Chifu, C. Pop, R. Suciu\",\"doi\":\"10.1109/ICCP.2012.6356160\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a firefly-based method for business process optimization. Each artificial firefly has a candidate business process associated which is modeled as a causal matrix. The evolution of a candidate business process is achieved using genetic operators which aim to perform structural and resource allocation modifications. To establish whether a candidate business process is optimal, the cost and the execution time of the process are evaluated using a penalty-based fitness function. The firefly-based method has been evaluated on a set of generic scenarios and its performance has been analyzed using the fitness graph evolutionary measure.\",\"PeriodicalId\":406461,\"journal\":{\"name\":\"2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE 8th International Conference on Intelligent Computer Communication and Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCP.2012.6356160\",\"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 IEEE 8th International Conference on Intelligent Computer Communication and Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCP.2012.6356160","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a firefly-based method for business process optimization. Each artificial firefly has a candidate business process associated which is modeled as a causal matrix. The evolution of a candidate business process is achieved using genetic operators which aim to perform structural and resource allocation modifications. To establish whether a candidate business process is optimal, the cost and the execution time of the process are evaluated using a penalty-based fitness function. The firefly-based method has been evaluated on a set of generic scenarios and its performance has been analyzed using the fitness graph evolutionary measure.