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Mathematical Problems in Engineering
Volume 2014, Article ID 638259, 14 pages
Research Article

Multipurpose Water Reservoir Management: An Evolutionary Multiobjective Optimization Approach

1Department of Thermal and Fluid Sciences, Federal University of São João del-Rei, 36307-352 São João del Rei, MG, Brazil
2Department of Mathematics, Federal University of Minas Gerais, 31270-901 Belo Horizonte, MG, Brazil
3Department of Mechanical Engineering, Federal University of São João del-Rei, 36307-352 São João del Rei, MG, Brazil

Received 23 January 2014; Revised 14 July 2014; Accepted 16 July 2014; Published 15 September 2014

Academic Editor: Xingsheng Gu

Copyright © 2014 Luís A. Scola et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The reservoirs that feed large hydropower plants should be managed in order to provide other uses for the water resources. Those uses include, for instance, flood control and avoidance, irrigation, navigability in the rivers, and other ones. This work presents an evolutionary multiobjective optimization approach for the study of multiple water usages in multiple interlinked reservoirs, including both power generation objectives and other objectives not related to energy generation. The classical evolutionary algorithm NSGA-II is employed as the basic multiobjective optimization machinery, being modified in order to cope with specific problem features. The case studies, which include the analysis of a problem which involves an objective of navigability on the river, are tailored in order to illustrate the usefulness of the data generated by the proposed methodology for decision-making on the problem of operation planning of multiple reservoirs with multiple usages. It is shown that it is even possible to use the generated data in order to determine the cost of any new usage of the water, in terms of the opportunity cost that can be measured on the revenues related to electric energy sales.