{"title":"大型水电建设项目粗糙随机MRCPSP双层规划模型","authors":"Zhe Zhang, Xiaoling Song","doi":"10.1504/ijads.2020.10024139","DOIUrl":null,"url":null,"abstract":"This paper focuses on developing a bi-level programming model for rough stochastic multi-mode resource constrained project scheduling problem (RS-MRCPSP/bi-level). The metal structure installation project (MSIP) in Wudongde Hydropower Station is considered as the prototype, and then it is extended to be a generalised bi-level MRCPSP. In the upper level, the construction contractor is responsible for the investment on the activity, while the outsourcing partner is in charge of construction and implementation in the lower level. In order to deal with the rough stochastic parameters, the rough stochastic expected value operator is employed. Subsequently, in order to obtain the optimal schedule, an interactive method-based passive congregation particle swarm optimisation (IM-based PCPSO) is designed. Finally, a practical application for MSIP is presented to highlight the practicability of proposed model and solution method.","PeriodicalId":216414,"journal":{"name":"Int. J. Appl. Decis. Sci.","volume":"601 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A bi-level programming model of rough stochastic MRCPSP in large-scale hydropower construction project\",\"authors\":\"Zhe Zhang, Xiaoling Song\",\"doi\":\"10.1504/ijads.2020.10024139\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper focuses on developing a bi-level programming model for rough stochastic multi-mode resource constrained project scheduling problem (RS-MRCPSP/bi-level). The metal structure installation project (MSIP) in Wudongde Hydropower Station is considered as the prototype, and then it is extended to be a generalised bi-level MRCPSP. In the upper level, the construction contractor is responsible for the investment on the activity, while the outsourcing partner is in charge of construction and implementation in the lower level. In order to deal with the rough stochastic parameters, the rough stochastic expected value operator is employed. Subsequently, in order to obtain the optimal schedule, an interactive method-based passive congregation particle swarm optimisation (IM-based PCPSO) is designed. Finally, a practical application for MSIP is presented to highlight the practicability of proposed model and solution method.\",\"PeriodicalId\":216414,\"journal\":{\"name\":\"Int. J. Appl. Decis. Sci.\",\"volume\":\"601 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Appl. Decis. Sci.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/ijads.2020.10024139\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Appl. Decis. Sci.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/ijads.2020.10024139","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A bi-level programming model of rough stochastic MRCPSP in large-scale hydropower construction project
This paper focuses on developing a bi-level programming model for rough stochastic multi-mode resource constrained project scheduling problem (RS-MRCPSP/bi-level). The metal structure installation project (MSIP) in Wudongde Hydropower Station is considered as the prototype, and then it is extended to be a generalised bi-level MRCPSP. In the upper level, the construction contractor is responsible for the investment on the activity, while the outsourcing partner is in charge of construction and implementation in the lower level. In order to deal with the rough stochastic parameters, the rough stochastic expected value operator is employed. Subsequently, in order to obtain the optimal schedule, an interactive method-based passive congregation particle swarm optimisation (IM-based PCPSO) is designed. Finally, a practical application for MSIP is presented to highlight the practicability of proposed model and solution method.