Multiobjective groundwater management using evolutionary algorithms

  • Authors:

  • Tobias Siegfried;Stefan Bleuler;Marco Laumanns;Eckart Zitzler;Wolfgang Kinzelbach

  • Affiliations:

  • Earth Institute, Columbia University, New York, NY;Computer Engineering and Networks Laboratory, Swiss Federal Institute of Technology, Zurich, Switzerland;Institute for Operations Research, Swiss Federal Institute of Technology, Zurich, Switzerland;Computer Engineering and Networks Laboratory, Swiss Federal Institute of Technology, Zurich, Switzerland;IFU, Institute of Environmental Engineering, Swiss Federal Institute of Technology, Zurich, Switzerland

  • Venue:
  • IEEE Transactions on Evolutionary Computation
  • Year:
  • 2009

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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.