Optimal Scheduling of Multiple Dam System Using Harmony Search Algorithm

  • Zong Woo Geem
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4507)


Musician’s behavior-inspired harmony search (HS) algorithm was first applied to the optimal operation scheduling of a multiple dam system. The HS model tackled a popular benchmark system with four dams. Results showed that the HS model found five different global optimal solutions with identical maximum benefit from hydropower generation and irrigation, while enhanced GA model (real-value coding, tournament selection, uniform crossover, and modified uniform mutation) found only near-optimal solutions under the same number of function evaluations. Furthermore, the HS model arrived at the global optima without performing any sensitivity analysis of algorithm parameters whereas the GA model required tedious sensitivity analysis.


Optimal Schedule Harmony Search Hydropower Generation Harmony Memory Pitch Adjust Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Oliveira, R., Loucks, D.P.: Operating Rules for Multireservoir Systems. Water Resources Research 33(4), 839–852 (1997)CrossRefGoogle Scholar
  2. 2.
    Chen, L.: Real Coded Genetic Algorithm Optimization of Long Term Reservoir Operation. Journal of the American Water Resources Association 39(5), 1157–1165 (2003)CrossRefGoogle Scholar
  3. 3.
    Esat, V., Hall, M.J.: Water Resources System Optimization Using Genetic Algorithms. In: Proceedings of the First International Conference on Hydroinformatics, pp. 225–231 (1994)Google Scholar
  4. 4.
    Wardlaw, R., Sharif, M.: Evaluation of Genetic Algorithms for Optimal Reservoir System Operation. Journal of Water Resources Planning and Management, ASCE 125(1), 25–33 (1999)CrossRefGoogle Scholar
  5. 5.
    Kim, T., Heo, J.-H., Jeong, C.-S.: Multireservoir System Optimization in the Han River basic using Multi-Objective Genetic Algorithm. Hydrological Processes 20, 2057–2075 (2006)CrossRefGoogle Scholar
  6. 6.
    Teegavarapu, R.S.V., Simonovic, S.P.: Optimal Operation of Reservoir Systems using Simulated Annealing. Water Resources Management 16, 401–428 (2002)CrossRefGoogle Scholar
  7. 7.
    Geem, Z.W., Kim, J.H., Loganathan, G.V.: A New Heuristic Optimization Algorithm: Harmony Search. Simulation 76(2), 60–68 (2001)CrossRefGoogle Scholar
  8. 8.
    Geem, Z.W.: Improved Harmony Search from Ensemble of Music Players. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds.) KES 2006. LNCS (LNAI), vol. 4251, pp. 86–93. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  9. 9.
    Lee, K.S., Geem, Z.W.: A New Structural Optimization Method Based on the Harmony Search Algorithm. Computers and Structures 82(9-10), 781–798 (2004)CrossRefGoogle Scholar
  10. 10.
    Geem, Z.W.: Optimal Cost Design of Water Distribution Networks using Harmony Search. Engineering Optimization 38(3), 259–280 (2006)CrossRefGoogle Scholar
  11. 11.
    Ryu, S., Duggal, A.S., Heyl, C.N., Geem, Z.W.: Mooring Cost Optimization Via Harmony Search. In: Proceedings of the 26th International Conference on Offshore Mechanics and Arctic Engineering, ASME. CD-ROM (2007)Google Scholar
  12. 12.
    Kim, J.H., Geem, Z.W., Kim, E.S.: Parameter Estimation of the Nonlinear Muskingum Model using Harmony Search. Journal of the American Water Resources Association 37(5), 1131–1138 (2001)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Zong Woo Geem
    • 1
  1. 1.Johns Hopkins University, Environmental Planning and Management Program, 729 Fallsgrove Drive #6133, Rockville, Maryland 20850USA

Personalised recommendations