| Project Scheduling Using Hybrid Genetic Algorithm with Fuzzy Logic Controller in SCM Environment |
| |
| 引用本文： | MitsuoGen KwanWooKim GenjiYamazaki. Project Scheduling Using Hybrid Genetic Algorithm with Fuzzy Logic Controller in SCM Environment[J]. 清华大学学报, 2003, 8(1): 19-29 |
| |
| 作者姓名： | MitsuoGen KwanWooKim GenjiYamazaki |
| |
| 作者单位： | [1]GraduateSchoolofInformation,Production＆Systems,WasedaUniversity,Kitakyushu808-0135,Japan [2]DepartmentofIntelligentSyStems,TokyoMetropolitanInstituteofTechnology,Hino-eity,Tokyo190-0065,Japan |
| |
| 摘 要： | In supply chain management (SCM) environment, we consider a resource-constrained project scheduling problem (rcPSP) model as one of advanced scheduling problems considered by a constraint programming technique. We develop a hybrid genetic algorithm (hGA) with a fuzzy logic controller (FLC) to solve the rcPSP which is the well known NP-hard problem. This new approach is based on the design of genetic operators with FLC through initializing the serial method which is superior for a large rcPSP scale. For solving these rcPSP problems, we first demonstrate that our hGA with FLC (flc-hGA) yields better results than several heuristic procedures presented in the literature. We have revealed a fact that flc-hGA has the evolutionary behaviors of average fitness better than hGA without FLC.
|
| 关 键 词： | 计划编制 混合遗传算法 模糊逻辑控制 供给链管理环境 rcPSP模型 规划方法 |
Project Scheduling Using Hybrid Genetic Algorithm with Fuzzy Logic Controller in SCM Environment |
| |
| Mitsuo Gen,KwanWoo Kim,Genji Yamazaki. Project Scheduling Using Hybrid Genetic Algorithm with Fuzzy Logic Controller in SCM Environment[J]. Tsinghua Science and Technology, 2003, 8(1): 19-29 |
| |
| Authors: | Mitsuo Gen KwanWoo Kim Genji Yamazaki |
| |
| Abstract: | In supply chain management (SCM) environment, we consider a resource-constrained project scheduling problem (rcPSP) model as one of advanced scheduling problems considered by a constraint programming technique. We develop a hybrid genetic algorithm (hGA) with a fuzzy logic controller (FLC) to solve the rcPSP which is the well known NP-hard problem. This new approach is based on the design of genetic operators with FLC through initializing the serial method which is superior for a large rcPSP scale. For solving these rcPSP problems, we first demonstrate that our hGA with FLC (flc-hGA) yields better results than several heuristic procedures presented in the literature. We have revealed a fact that flc-hGA has the evolutionary behaviors of average fitness better than hGA without FLC. |
| |
| Keywords: | resource-constrained project scheduling problem (rcPSP) priority rule method (PRM) hybrid genetic algorithm (hGA) fuzzy logic controller (FLC) |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
