Abstract
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.
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References
Oliveira, R., Loucks, D.P.: Operating Rules for Multireservoir Systems. Water Resources Research 33(4), 839–852 (1997)
Chen, L.: Real Coded Genetic Algorithm Optimization of Long Term Reservoir Operation. Journal of the American Water Resources Association 39(5), 1157–1165 (2003)
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)
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)
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)
Teegavarapu, R.S.V., Simonovic, S.P.: Optimal Operation of Reservoir Systems using Simulated Annealing. Water Resources Management 16, 401–428 (2002)
Geem, Z.W., Kim, J.H., Loganathan, G.V.: A New Heuristic Optimization Algorithm: Harmony Search. Simulation 76(2), 60–68 (2001)
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)
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)
Geem, Z.W.: Optimal Cost Design of Water Distribution Networks using Harmony Search. Engineering Optimization 38(3), 259–280 (2006)
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)
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)
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Geem, Z.W. (2007). Optimal Scheduling of Multiple Dam System Using Harmony Search Algorithm. In: Sandoval, F., Prieto, A., Cabestany, J., Graña, M. (eds) Computational and Ambient Intelligence. IWANN 2007. Lecture Notes in Computer Science, vol 4507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73007-1_39
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DOI: https://doi.org/10.1007/978-3-540-73007-1_39
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