An interval-parameter fuzzy linear programming with stochastic vertices model for water resources management under uncertainty
文献类型：EI期刊论文
| 作者 | Jia Shaofeng; Han Yan |
| 发表日期 | 2013 |
| 关键词 | Water resources Linear programming Neural networks Optimization Stochastic models Stochastic programming Stochastic systems Water supply |
| 英文摘要 | An interval-parameter fuzzy linear programming with stochastic vertices (IFLPSV) method is developed for water resources management under uncertainty by coupling interval-parameter fuzzy linear programming (IFLP) with stochastic programming (SP). As an extension of existing interval parameter fuzzy linear programming, the developed IFLPSV approach has advantages in dealing with dual uncertainty optimization problems, which uncertainty presents as interval parameter with stochastic vertices in both of the objective functions and constraints. The developed IFLPSV method improves upon the IFLP method by allowing dual uncertainty parameters to be incorporated into the optimization processes. A hybrid intelligent algorithm based on genetic algorithm and artificial neural network is used to solve the developed model. The developed method is then applied to water resources allocation in Beijing city of China in 2020, where water resources shortage is a challenging issue. The results indicate that reasonable solutions have been obtained, which are helpful and useful for decision makers. Although the amount of water supply from Guanting and Miyun reservoirs is declining with rainfall reduction, water supply from the South-to-North Water Transfer project will have important impact on water supply structure of Beijing city, particularly in dry year and extraordinary dry year. 2013 Yan Han et al. |
| 出处 | Mathematical Problems in Engineering
 |
| 卷 | 2013 |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/31264]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Jia Shaofeng,Han Yan. An interval-parameter fuzzy linear programming with stochastic vertices model for water resources management under uncertainty. 2013. |
入库方式： OAI收割
来源：地理科学与资源研究所
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