JOURNAL BROWSE
Search
Advanced SearchSearch Tips
Development and Applications of Multi-layered Harmony Search Algorithm for Improving Optimization Efficiency
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
Development and Applications of Multi-layered Harmony Search Algorithm for Improving Optimization Efficiency
Lee, Ho Min; Yoo, Do Guen; Lee, Eui Hoon; Choi, Young Hwan; Kim, Joong Hoon;
  PDF(new window)
 Abstract
The Harmony Search Algorithm (HSA) is one of the recently developed metaheuristic optimization algorithms. Since the development of HSA, it has been applied by many researchers from various fields. The increasing complexity of problems has created enormous challenges for the current technique, and improved techniques of optimization algorithms are required. In this study, to improve the HSA in terms of a structural setting, a new HSA that has structural characteristics, called the Multi-layered Harmony Search Algorithm (MLHSA) was proposed. In this new method, the structural characteristics were added to HSA to improve the exploration and exploitation capability. In addition, the MLHSA was applied to optimization problems, including unconstrained benchmark functions and water distribution system pipe diameter design problems to verify the efficiency and applicability of the proposed algorithm. The results revealed the strength of MLHSA and its competitiveness.
 Keywords
Harmony Search Algorithm;Metaheuristic;Multi-layered Harmony Search Algorithm;Optimization;Water Distribution System;
 Language
Korean
 Cited by
 References
1.
Holland J. H. Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence. U Michigan Press, 1975.

2.
Glover F. "Heuristics for integer programming using surrogate constraints." Decision Sciences 8.1 (1977): 156-166. DOI: http://dx.doi.org/10.1111/j.1540-5915.1977.tb01074.x crossref(new window)

3.
Kirkpatrick S. and Vecchi M. P. "Optimization by simmulated annealing." science 220.4598 (1983): 671-680. crossref(new window)

4.
Dorigo M. "Optimization, learning and natural algorithms." Ph. D. Thesis, Politecnico di Milano, Italy (1992).

5.
Eberhart R. C. and Kennedy J. "A new optimizer using particle swarm theory." Proceedings of the sixth international symposium on micro machine and human science. Vol. 1. 1995. DOI: http://dx.doi.org/10.1109/MHS.1995.494215 crossref(new window)

6.
Storn R. and Kenneth V. "Minimizing the Real Functions of the ICEC'96 Contest by Differential Evolution." International Conference on Evolutionary Computation. 1996. DOI: http://dx.doi.org/10.1109/ICEC.1996.542711 crossref(new window)

7.
Geem Z. W., Kim J. H. and Loganathan G. V. "A new heuristic optimization algorithm: harmony search." Simulation 76.2 (2001): 60-68. DOI: http://dx.doi.org/10.1177/003754970107600201 crossref(new window)

8.
Nakrani S. and Tovey C. "On honey bees and dynamic server allocation in internet hosting centers." Adaptive Behavior 12.3-4 (2004): 223-240. crossref(new window)

9.
Yang X. S. and Deb S. "Engineering optimisation by cuckoo search." International Journal of Mathematical Modelling and Numerical Optimisation 1.4 (2010): 330-343. DOI: http://dx.doi.org/10.1504/IJMMNO.2010.035430 crossref(new window)

10.
Yang X. S. "A new metaheuristic bat-inspired algorithm." Nature inspired cooperative strategies for optimization (NICSO 2010b). Springer Berlin Heidelberg, 2010. 65-74.3.

11.
Eskandar H., Sadollah A., Bahreininejad A. and Hamdi M. "Water cycle algorithm-A novel metaheuristic optimization method for solving constrained engineering optimization problems." Computers & Structures 110 (2012): 151-166. DOI: http://dx.doi.org/10.1016/j.compstruc.2012.07.010 crossref(new window)

12.
Sadollah A., Bahreininejad A., Eskandar H. and Hamdi M. "Mine blast algorithm for optimization of truss structures with discrete variables." Computers & Structures 102 (2012): 49-63. DOI: http://dx.doi.org/10.1016/j.compstruc.2012.03.013 crossref(new window)

13.
Paik K. "Development of seasonal tank model and comparison of optimization algorithms for parameter calibration." Master Degree Dissertation, Department of Civil and Environmental Engineering, Korea University, Seoul, Korea (2001).

14.
Baek C. W. "Development of Optimal Decision-Making System for Rehabilitation of Water Distribution Systems Using ReHS" Master Degree Dissertation, Department of Civil and Environmental Engineering, Korea University, Seoul, Korea (2002).

15.
Geem Z. W.,Tseng C. and Park Y. "Harmony search for generalized orienteering problem: best touring in China." Advances in natural computation. Springer Berlin Heidelberg, (2005): 741-750.

16.
Geem Z. W. "Improved harmony search from ensemble of music players." Knowledge-Based Intelligent Information and Engineering Systems. Springer Berlin Heidelberg, (2006): 86-93. DOI: http://dx.doi.org/10.1007/11892960_11 crossref(new window)

17.
Mahdavi M., Fesanghary M., and Damangir E. "An improved harmony search algorithm for solving optimization problems." Applied mathematics and computation, 188.2 (2007): 1567-1579. DOI: http://dx.doi.org/10.1016/j.amc.2006.11.033 crossref(new window)

18.
Omran M. G. and Mahdavi M. "Global-best harmony search." Applied Mathematics and Computation 198.2 (2008): 643-656. DOI: http://dx.doi.org/10.1016/j.amc.2007.09.004 crossref(new window)

19.
Chakraborty P., Roy G. G., Das S., Jain D. and Abraham A "An Improved Harmony Search Algorithm with Differential Mutation Operator." Fundam. Inform. 95.4 (2009): 401-426.

20.
Hasancebi O., Erdal F. and Saka M. P. "Adaptive harmony search method for structural optimization." Journal of Structural Engineering 136.4 (2009): 419-431. (2009): 79-120.

21.
Wang C. M. and Huang Y. F. "Self-adaptive harmony search algorithm for optimization." Expert Systems with Applications 37.4 (2010): 2826-2837. DOI: http://dx.doi.org/10.1016/j.eswa.2009.09.008 crossref(new window)

22.
Al-Betar M. A., Khader A. T. and Liao I. Y. "A harmony search with multi-pitch adjusting rate for the university course timetabling." Recent advances in Harmony search algorithm. Springer Berlin Heidelberg, (2010): 147-161.

23.
Geem Z. W. and Sim K. B. "Parameter-setting-free harmony search algorithm." Applied Mathematics and Computation 217.8 (2010): 3881-3889. DOI: http://dx.doi.org/10.1016/j.amc.2010.09.049 crossref(new window)

24.
Fesanghary M., Mahdavi M., Minary-Jolandan M. and Alizadeh, Y. "Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems." Computer methods in applied mechanics and engineering 197.33 (2008): 3080-3091. DOI: http://dx.doi.org/10.1016/j.cma.2008.02.006 crossref(new window)

25.
Mahdavi M., Chehreghani M. H., Abolhassani H. and Forsati R. "Novel meta-heuristic algorithms for clustering web documents." Applied Mathematics and Computation 201.1 (2008): 441-451. DOI: http://dx.doi.org/10.1016/j.amc.2007.12.058 crossref(new window)

26.
Forsati R., Mahdavi M., Kangavari M. and Safarkhani B. "Web page clustering using harmony search optimization." Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on. IEEE, 2008. DOI: http://dx.doi.org/10.1109/ccece.2008.4564812 crossref(new window)

27.
Malaki M., Pourbaghery J. A. and Abolhassani H. "A Combinatiory Approach to Fuzzy Clustering with Harmony Search and its Applications to Space Shuttle data." SCIS & ISIS. Vol. 2008. No. 0. Japan Society for Fuzzy Theory and Intelligent Informatics, 2008.

28.
Jang W. S., Kang H. I. and Lee B. H. "Hybrid simplex-harmony search method for optimization problems." 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence). 2008. DOI: http://dx.doi.org/10.1109/cec.2008.4631365 crossref(new window)

29.
Geem Z. W. "Particle-swarm harmony search for water network design." Engineering Optimization 41.4 (2009): 297-311. DOI: http://dx.doi.org/10.1080/03052150802449227 crossref(new window)

30.
Wang X., Gao X. Z. and Ovaska S. J. "Fusion of clonal selection algorithm and harmony search method in optimisation of fuzzy classification systems." International Journal of Bio-Inspired Computation 1.1-2 (2009): 80-88. crossref(new window)

31.
Zou D., Gao L., Wu J., Li, S. and Li Y. "A novel global harmony search algorithm for reliability problems." Computers & Industrial Engineering 58.2 (2010): 307-316. DOI: http://dx.doi.org/10.1016/j.cie.2009.11.003 crossref(new window)

32.
Im S. S., Yoo D. G. and Kim J. H. "Smallest-small-world cellular harmony search for optimization of unconstrained benchmark problems." Journal of Applied Mathematics 2013 (2013). DOI: http://dx.doi.org/10.1155/2013/635608 crossref(new window)

33.
Al-Betar M. A., Khader A. T., Awadallah M. A., Alawan M. H. and Zaqaibeh B. "Cellular harmony search for optimization problems." Journal of Applied Mathematics 2013 (2013). DOI: http://dx.doi.org/10.1155/2013/139464 crossref(new window)

34.
Simpson A., Dandy G. and Murphy L. "Genetic algorithms compared to other techniques for pipe optimisation." Journal of Water Resources Planning and Management 120.4 (1994): 423-443. DOI: http://dx.doi.org/10.1061/(ASCE)0733-9496(1994)120:4(423) crossref(new window)

35.
Dandy G., Simpson, A. and Murphy L. "An improved genetic algorithm for pipe network optimisation." Water Resources Research 32.2 (1996): 449-458. DOI: http://dx.doi.org/10.1029/95WR02917 crossref(new window)

36.
Maier H., Simpson A., Zecchin A., Foong W., Phang K., Seah H. and Tan, C. "Ant colony optimization for design of water distribution systems," Journal of Water Resources Planning and Management 129.3 (2003): 200-209. DOI: http://dx.doi.org/10.1061/(ASCE)0733-9496(2003)129:3(200) crossref(new window)

37.
Suribabu C. R. and Neelakantan T. R. "Design of water distribution networks using particle swarm optimization." Urban Water Journal 3.2 (2006): 111-120. DOI: http://dx.doi.org/10.1080/15730620600855928 crossref(new window)

38.
Montalvo I., Izquierdo J., Perez R. and Tung, M. M. "Particle swarm optimization applied to the design of water supply systems." Computers and Mathematics with Applications 56 (2008): 769-776. DOI: http://dx.doi.org/10.1016/j.camwa.2008.02.006 crossref(new window)

39.
Geem, Z. W. "Optimal cost design of water distribution networks using harmony search." Engineering Optimization 38 (2006): 3,259-277.

40.
Vasan A. and Simonovic S. P. "Optimization of water distribution network design using differential evolution." Journal of Water Resources Planning and Management 136.2 (2010): 279-287. DOI: http://dx.doi.org/10.1061/(ASCE)0733-9496(2010)136:2(279) crossref(new window)

41.
Reca J. and Martinez J. "Genetic algorithms for the design of looped irrigation water distribution networks." Water Resources Research 42.5 (2006).

42.
Reca J., Martinez J., Gil C., and Banos R. "Application of several meta-heuristic techniques to the optimization of real looped water distribution networks." Water Resources Management 22.10 (2007): 1367-1379. DOI: http://dx.doi.org/10.1007/s11269-007-9230-8 crossref(new window)

43.
Bolognesi A., Bragalli C., Marchi A. and Artina, S. "Genetic heritage evolution by stochastic transmission in the optimal design of water distribution networks." Advances in Engineering Software 41 (2010): 792.801. crossref(new window)

44.
Sadollah A., Yoo D. G. and Kim J. H. "Improved mine blast algorithm for optimal cost design of water distribution systems." Engineering Optimization ahead-of-print (2014) 1-17.