Multiobjective Groundwater Management Using Evolutionary Algorithms

被引:19
|
作者
Siegfried, Tobias [1 ]
Bleuler, Stefan [2 ]
Laumanns, Marco [3 ]
Zitzler, Eckart [2 ]
Kinzelbach, Wolfgang [4 ]
机构
[1] Columbia Univ, Earth Inst, New York, NY 10027 USA
[2] ETH, Swiss Fed Inst Technol, Comp Engn & Networks Lab, TIK, CH-8092 Zurich, Switzerland
[3] ETH, Swiss Fed Inst Technol, IFOR, CH-8092 Zurich, Switzerland
[4] ETH, Swiss Fed Inst Technol, Inst Environm Engn, IFU, CH-8092 Zurich, Switzerland
关键词
Benchmark application; economic externalities; groundwater management; multiobjective evolutionary algorithm; Pareto set approximation; PISA; MONITORING DESIGN; REMEDIATION; OPTIMIZATION;
D O I
10.1109/TEVC.2008.923391
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Sustainable management of groundwater resources is of crucial importance for regions where freshwater supply is naturally limited. Long-term planning of groundwater usage requires computer-based decision support tools: on the one hand, they must be able to predict I he complex system dynamics with sufficient accuracy, on the other, they must: allow exploring management scenarios with respect: to different criteria such as sustainability, cost, etc. In this paper, we present a multiobjective evolutionary algorithm for groundwater management that optimizes the placement and the operation of pumping facilities over time, while considering multiple neighboring regions which are economically independent. The algorithm helps in investigating the cost tradeoffs; between the different regions by providing an approximation of the Pareto-optimal set, and its capabilities are demonstrated on a three-region problem. The application of the proposed methodology can also serve as a benchmark problem as shown in this paper. The corresponding implementation is freely available as a precompiled module at http://www.tik.ee.ethz.ch/pisa.
引用
收藏
页码:229 / 242
页数:14
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