Node ordinal encoded genetic algorithm for the optimal allocation of water resources |
| |
作者姓名: | YANG Xiaohu YANG Zhifeng SHEN Zhenyao LI Jianqiang |
| |
作者单位: | State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China,State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China;Key Laboratory for Water and Sediment Sciences Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, China;,State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China,Water Resources and Hydropower Planning and Design General Institute, MWR, Beijing 100011, China |
| |
摘 要: | A new method, node ordinal encoded genetic algorithm (NOEGA), is proposed for solving water resources optimal allocation problems, in which the capacity of water resources is split into a number of smaller parts so that successive operations can be overlapped. Our objective is to maximize the whole benefit function. To overcome the “dimensionality and algorithm complexity curse” while searching for solutions and looking for an optimal solution, the operations of one-point crossover operator, gene exchange operator, gene random operator, gene shift operator and node ordinal strings are established. It is proved to be an effective optimal method in searching for global solutions. The NOEGA does not need a diversity of initial population, and it does not have the problem of immature convergence. The results of two cases show that using NOEGA to solve the optimal allocation model is very efficient and robust. In addition, the algorithm complexity of NOEGA is discussed.
|
关 键 词: | water resources optimal allocation node ordinal code genetic algorithm. |
|
| 点击此处可从《自然科学进展(英文版)》浏览原始摘要信息 |
|
点击此处可从《自然科学进展(英文版)》下载全文 |
|