JOURNAL ARTICLE

Multiobjective Groundwater Management Using Evolutionary Algorithms

Tobias SiegfriedStefan BleulerMarco LaumannsEckart ZitzlerWolfgang Kinzelbach

Year: 2008 Journal:   IEEE Transactions on Evolutionary Computation Vol: 13 (2)Pages: 229-242   Publisher: Institute of Electrical and Electronics Engineers

Abstract

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 the 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.

Keywords:
Benchmark (surveying) Evolutionary algorithm Computer science Pareto principle Pareto optimal Multi-objective optimization Mathematical optimization Set (abstract data type) Evolutionary computation Sustainability Operations research Machine learning Mathematics Ecology

Metrics

48
Cited By
4.68
FWCI (Field Weighted Citation Impact)
42
Refs
0.94
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Water resources management and optimization
Physical Sciences →  Engineering →  Ocean Engineering
Water Systems and Optimization
Physical Sciences →  Engineering →  Civil and Structural Engineering
Advanced Multi-Objective Optimization Algorithms
Physical Sciences →  Computer Science →  Computational Theory and Mathematics

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