Hybrid Harmony Search Algorithm for Global Optimization Problems

Abstract:

Harmony search (HS) algorithm is a new population based algorithm, which imitates the phenomenon of musical improvisation process. Its own potential and shortage, one shortage is that it easily trapped into local optima. In this paper, a hybrid harmony search algorithm (HHS) is proposed based on the conception of swarm intelligence. HHS employed a local search method to replace the pitch adjusting operation, and designed an elitist preservation strategy to modify the selection operation. Experiment results demonstrated that the proposed method performs much better than the HS and its improved algorithms (IHS, GHS and NGHS).

• Periodical: Advanced Materials Research (Volumes 1065-1069)
• Pages: 3438-3441
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.1065-1069.3438
• Online since: December 2014
• Authors: Guo Jun Li*
• Keywords: Elitist Preservation, Harmony Search Algorithm, Local Search, Swarm Intelligence

References

[1] He Y H, Hui C W. A binary coding genetic algorithm for multi-purpose process scheduling: A case study [J], Chemical Engineering Science, 2010, 65(16): 4816-4828.

DOI: 10.1016/j.ces.2010.05.032

[2] Shi H X. Solution to 0/1 knapsack problem based on improved ant colony algorithm [C], in: International Conference on Information Acquisition, 2006, 1062-1066.

DOI: 10.1109/icia.2006.305887

[3] Coelho L S. An efficient particle swarm approach for mixed-integer programming in reliability–redundancy optimization applications [J], Reliability Engineering & System Safety, 2009, 94(4): 830-837.

DOI: 10.1016/j.ress.2008.09.001

[4] Onwubolu G, Davendra D. Scheduling flow shops using differential evolution algorithm [J], European Journal of Operational Research, 2006, 171(2): 674-692.

DOI: 10.1016/j.ejor.2004.08.043

[5] Geem Z W, Kim J H, Loganathan G V. A new heuristic optimization algorithm: harmony search. Simulation, 2001, 76(2): 60-68.

DOI: 10.1177/003754970107600201

[6] Saka M P, Optimum design of steel sway frames to BS5950 using harmony search algorithm. Constructional Steel Research, 2009, 65(1): 36-43.

DOI: 10.1016/j.jcsr.2008.02.005

[7] M Mahdavi, M Fesanghary, E Damangir. An improve harmony search algorithm for solving optimization problems. Applied Mathematics and Computation 2007; 188(2) 1567-1579.

DOI: 10.1016/j.amc.2006.11.033

[8] Ayvaz M T. Application of Harmony Search algorithm to the solution of groundwater management models. Advances in Water Resources, 2009, 32(6): 916-924.

DOI: 10.1016/j.advwatres.2009.03.003

[9] Geem Z W, Lee K S, Park Y J. Application of harmony search to vehicle routing. American Journal of Applied Sciences, 2005, 12(2): 1552–1557.

DOI: 10.3844/ajassp.2005.1552.1557

[10] J H Kim, Z W Geem, E S Kim, Parameter estimation of the nonlinear Muskingum model using harmony search, Journal of American Water Resource Association, 2001, 37(5) 1131–1138.

DOI: 10.1111/j.1752-1688.2001.tb03627.x

[11] Geem Z W. Particle-swarm harmony search for water network design [J], Engineering Optimization, 2009, 41(4): 297-311.

DOI: 10.1080/03052150802449227

[12] Sharma K D, Chatterjee A, Rakshit A. Design of a Hybrid Stable Adaptive Fuzzy Controller Employing Lyapunov Theory and Harmony Search Algorithm [J], IEEE Transactions on Control Systems Technology, 2010, PP(99): 1-8.

DOI: 10.1109/tcst.2009.2039138

[13] Chia-Ming Wang, Yin-Fu Huang. Self-adaptive harmony search algorithm for optimization. Expert Systems with Applications, 2010, 37(4): 2826-2837.

DOI: 10.1016/j.eswa.2009.09.008

[14] Omran M G H, Mahdavi M. Global-best harmony search [J], Applied Mathematics and Computation, 2008, 198(2): 643-656.

DOI: 10.1016/j.amc.2007.09.004

[15] Zou D X, Gao L Q, Wu J H, Li S. Novel global harmony search algorithm for unconstrained problems [J], Neurocomputing, 2010, 73(16-18): 3308-3318.

DOI: 10.1016/j.neucom.2010.07.010