Water Resources Management

, Volume 19, Issue 6, pp 831–848 | Cite as

Multi-Reservoir Operation Planning Using Hybrid Genetic Algorithm and Linear Programming (GA-LP): An Alternative Stochastic Approach

  • L. F. R. ReisEmail author
  • G. A. Walters
  • D. Savic
  • F. H. Chaudhry


Many models have been suggested to deal with the multi-reservoir operation planning stochastic optimization problem involving decisions on water releases from various reservoirs in different time periods of the year. A new approach using genetic algorithm (GA) and linear programming (LP) is proposed here to determine operational decisions for reservoirs of a hydro system throughout a planning period, with the possibility of considering a variety of equally likely hydrologic sequences representing inflows. This approach permits the evaluation of a reduced number of parameters by GA and operational variables by LP. The proposed algorithm is a stochastic approximation to the hydro system operation problem, with advantages such as simple implementation and the possibility of extracting useful parameters for future operational decisions. Implementation of the method is demonstrated through a small hypothetical hydrothermal system used in literature as an example for stochastic dual dynamic programming (SDDP) method of Pereira and Pinto (Pereira, M. V. F. and Pinto, L. M. V. G.: 1985, Water Res. Res. 21(6), 779–792). The proposed GA-LP approach performed equally well as compared to the SDDP method.


genetic algorithm hydrothermal system linear programming multi-reservoir systems optimal operation power generation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Cai, X., Mckinney, D., and Lasdon, L. S., 2001, ‘Solving nonlinear water management models using a combined genetic algorithm and linear programming approach’, Adv. Water Resour. 2(6), 667–676.Google Scholar
  2. Labadie, J. W., 2004, ‘Optimal operation of multireservoir systems: State-of-the-art review’, J. Water Res. Plan. Manage. ASCE 130(2), 93–111.Google Scholar
  3. Loucks, D. P., Stedinger, J. R., and Haith, J. R., 1981, Water Resource Systems Planning and Analysis, Prentice-Hall, Englewood Cliffs, NJ.Google Scholar
  4. Oliveira, R. and Loucks, D. P., 1997, ‘Operating rules for multi-reservoir systems’, Water Res. Res. 33(4), 839–852.CrossRefGoogle Scholar
  5. Pereira, M. V. F. and Pinto, L. M. V. G., 1985, ‘Stochastic optimization of a multi-reservoir hydroelectric system: A decomposition approach’, Water Res. Res. 21(6), 779–792.Google Scholar
  6. Pereira, M. V. F. and Pinto, L. M. V. G., 1988, ‘Multi-stage stochastic optimization applied to energy planning’, in Workshop on Mathematical Programming, Pontifícia Universidade Católica, Rio de Janeiro (in Portuguese).Google Scholar
  7. Pinheiro, T. M., 2003, ‘A Study of Optimized Reservoir System Operation by Hybrid GA-LP Approach considering Evaporation’, Masters Dissertation, Sao Carlos School of Engineering, University of Sao Paulo, Sao Carlos, SP, Brazil (in Portuguese).Google Scholar
  8. Reis, L. F. R. and Chaudhry, F. H., 1994, ‘Stochastic characterization of optimal response of a hydroelectric system via dynamic programming’, in Keith W. Hipel (ed), Stochastic and Statistical Modelling with Groundwater and Surface Water Applications, Kluwer Academic, Netherlands.Google Scholar
  9. Saad, M. and Turgeon, A., 1988, ‘Application of principal component analysis to long-term reservoir management’, Water Res. Res. 24(7), 907–1192.Google Scholar
  10. Seifi, A. and Hipel, K. W., 2001, ‘Interior-point method for reservoir operation with stochastic inflows’, J. Water Res. Plan. Manage. ASCE 127(1), 48–57.Google Scholar
  11. Sharif, M. and Wardlaw, R., 2000, ‘Multi-reservoir systems optimization using genetic algorithm: Case study’, J. Comp. Civil Eng. 14(4), 255–263.Google Scholar
  12. Wardlaw, R. and Sharif, M., 1999, ‘Evaluation of genetic algorithms for optimal reservoir system operation’, J. Water Res. Plan. Manage. ASCE 125(1), 25–33.Google Scholar
  13. Wurbs, R., 1993, ‘Reservoir-system simulation and optimization models’, J. Water Res. Plan. Manage. ASCE 119(4), 455–472.Google Scholar
  14. Yeh, W., 1985, ‘Reservoir management and operation models: A state-of-the-art review’, Water Res. Res. 21(12), 1797–1818.Google Scholar

Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • L. F. R. Reis
    • 1
    Email author
  • G. A. Walters
    • 2
  • D. Savic
    • 2
  • F. H. Chaudhry
    • 1
  1. 1.São Carlos School of EngineeringUniversity of São PauloSão CarlosBrazil
  2. 2.Department of Engineering, School of Engineering and Computer ScienceUniversity of ExeterExeterU.K.

Personalised recommendations