Abstract
Parallel Harmony Search (PHS) is a harmony search variant that employs parallel computing approach for improving the final solution quality of harmony search. A preliminary version of PHS was introduced in 2015 and applied to a highly nonlinear water infrastructure planning problem with extreme dimensionality. The application results showed that the PHS was promising and efficient in finding a feasible and near-optimal solution for such problem. However, sensitivity analysis on migration parameters of PHS should be performed to guarantee the best performance of PHS. Migration parameters of interest are migration frequency, migration topology, migration size, and so forth. In this study, PHSs with different migration frequencies are compared with respect to the final solution quality to identify the most efficient frequency in the water infrastructure planning problem.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Elfeky, E.Z., Sarker, R., Essam, D.L.: Partial decomposition and parallel GA (PD-PGA) for constrained optimization. In: IEEE International Conference on Systems, Man and Cybernetics, pp. 220–227 (2008)
Artina, S., Bragalli, C., Erbacci, G., Marchi, A., Rivi, M.: Contribution of parallel NSGA-II in optimal design of water distribution networks. J. Hydroinformatics 14(2), 310–323 (2012)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.A.M.T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)
Abu-Lebdeh, G., Chen, H., Ghanim, M.: Improving performance of genetic algorithms for transportation systems: case of parallel genetic algorithms. J. Infrastruct. Syst. A4014002 (2014)
Jung, D., Choi, J., Choi, Y.H., Kim, J.H.: A new parallelization scheme for harmony search algorithm. In: Kim, J.H., Geem, Z.W. (eds.) Harmony Search Algorithm. AISC, vol. 382, pp. 147–152. Springer, Heidelberg (2016). doi:10.1007/978-3-662-47926-1_15
Geem, Z.W., Kim, J.H., Loganathan, G.V.: A new heuristic optimization algorithm: harmony search. Simulation 76(2), 60–68 (2001)
Kim, J.H., Geem, Z.W., Kim, E.S.: Parameter estimation of the nonlinear muskingum model using harmony search. J. Am. Water Res. Assoc. 37(5), 1131–1138 (2001)
Acknowledgements
This subject is supported by Korea Ministry of Environment as Global Top Project (2016002120004).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Hong, A., Jung, D., Choi, J., Kim, J.H. (2017). Sensitivity Analysis on Migration Parameters of Parallel Harmony Search. In: Del Ser, J. (eds) Harmony Search Algorithm. ICHSA 2017. Advances in Intelligent Systems and Computing, vol 514. Springer, Singapore. https://doi.org/10.1007/978-981-10-3728-3_1
Download citation
DOI: https://doi.org/10.1007/978-981-10-3728-3_1
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-3727-6
Online ISBN: 978-981-10-3728-3
eBook Packages: EngineeringEngineering (R0)