{"title":"A MODM Bi-level Model with Fuzzy Random Coefficients for Resource-Constrained Project Scheduling Problems","authors":"Zhe Zhang","doi":"10.1109/CSO.2014.123","DOIUrl":null,"url":null,"abstract":"The aim of this paper is to solve resource-constrained projects scheduling problems (RCPSP) with complex hierarchical organization structure. A bi-level MODM model with fuzzy random coefficients is developed for RCPSP under hybrid uncertainty environment. In this model, construction contractor is considered as the upper level decision maker (ULDM) and outsourcing partner is the lower level decision maker (LLDM). The bi-level multiple objective particle swarm optimization algorithm (BL-MOPSO) is designed to obtain the optimal schedule. An illustrative example is given in order to show the effectiveness of the proposed model and algorithm.","PeriodicalId":174800,"journal":{"name":"2014 Seventh International Joint Conference on Computational Sciences and Optimization","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Seventh International Joint Conference on Computational Sciences and Optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSO.2014.123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
The aim of this paper is to solve resource-constrained projects scheduling problems (RCPSP) with complex hierarchical organization structure. A bi-level MODM model with fuzzy random coefficients is developed for RCPSP under hybrid uncertainty environment. In this model, construction contractor is considered as the upper level decision maker (ULDM) and outsourcing partner is the lower level decision maker (LLDM). The bi-level multiple objective particle swarm optimization algorithm (BL-MOPSO) is designed to obtain the optimal schedule. An illustrative example is given in order to show the effectiveness of the proposed model and algorithm.