zbMATH — the first resource for mathematics

Geometry Search for the term Geometry in any field. Queries are case-independent.
Funct* Wildcard queries are specified by * (e.g. functions, functorial, etc.). Otherwise the search is exact.
"Topological group" Phrases (multi-words) should be set in "straight quotation marks".
au: Bourbaki & ti: Algebra Search for author and title. The and-operator & is default and can be omitted.
Chebyshev | Tschebyscheff The or-operator | allows to search for Chebyshev or Tschebyscheff.
"Quasi* map*" py: 1989 The resulting documents have publication year 1989.
so: Eur* J* Mat* Soc* cc: 14 Search for publications in a particular source with a Mathematics Subject Classification code (cc) in 14.
"Partial diff* eq*" ! elliptic The not-operator ! eliminates all results containing the word elliptic.
dt: b & au: Hilbert The document type is set to books; alternatively: j for journal articles, a for book articles.
py: 2000-2015 cc: (94A | 11T) Number ranges are accepted. Terms can be grouped within (parentheses).
la: chinese Find documents in a given language. ISO 639-1 language codes can also be used.

a & b logic and
a | b logic or
!ab logic not
abc* right wildcard
"ab c" phrase
(ab c) parentheses
any anywhere an internal document identifier
au author, editor ai internal author identifier
ti title la language
so source ab review, abstract
py publication year rv reviewer
cc MSC code ut uncontrolled term
dt document type (j: journal article; b: book; a: book article)
Hybrid harmony search and artificial bee colony algorithm for global optimization problems. (English) Zbl 1268.90164
Summary: Harmony search (HS) is one of the newest and the easiest to code music inspired heuristics for optimization problems. In order to enhance the accuracy and convergence rate of harmony search, a hybrid harmony search is proposed by incorporating the artificial bee colony algorithm (ABC). The artificial bee colony algorithm is a new swarm intelligence technique inspired by intelligent foraging behavior of honey bees. The ABC and its variants are used to improve harmony memory (HM). To compare and analyze the performance of our proposed hybrid algorithms, a number of experiments are carried out on a set of well-known benchmark global optimization problems. The effects of the parameters about the hybrid algorithms are discussed by a uniform design experiment. Numerical results show that the proposed algorithms can find better solutions when compared to HS and other heuristic algorithms and are powerful search algorithms for various global optimization problems.

90C59Approximation methods and heuristics
90C26Nonconvex programming, global optimization
Full Text: DOI
[1] Geem, Z. W.; Kim, J. H.; Loganathan, G. V.: A new heuristic optimization algorithm: harmony search, Simulations 76, 60-68 (2001)
[2] Mahdavi, M.; Fesanghary, M.; Damangir, E.: An improved harmony search algorithm for solving optimization problems, Appl. math. Comput. 188, 1567-1579 (2007) · Zbl 1119.65053 · doi:10.1016/j.amc.2006.11.033
[3] Lee, K. S.; Geem, Z. W.; Lee, S. H.; Bae, K. -W.: The harmony search heuristic algorithm for discrete structural optimization, Eng. optim. 37, 663-684 (2005)
[4] Geem, Z. W.: Optimal cost design of water distribution networks using harmony search, Eng. optim. 38, 259-280 (2006)
[5] Geem, Z. W.: Harmony search algorithm for solving sudoku, Part I. LNCS (LNAI), vol. 4692 4692, 371-378 (2007)
[6] Forsati, R.; Haghighat, A. T.; Mahdavi, M.: Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing, Comput. commun. 31, 2505-2519 (2008)
[7] Ceylan, H.; Haldenbilen, S.: Transport energy modeling with meta-heuristic harmony search algorithm, an application to Turkey, Energy policy 36, 2527-2535 (2008)
[8] Saka, M. P.; Erdal, F.: Harmony search based algorithm for the optimum design of grillage systems to LRFD-AISC, Struct. multidiscip. Optim. 38, 25-41 (2009)
[9] Mun, S.; Geem, Z. W.: Determination of individual sound power levels of noise sources using a harmony search algorithm, Int. J. Indust. ergon. 39, 366-370 (2009)
[10] Coelho, L. D.; Mariani, V. C.: An improved harmony search algorithm for power economic load dispatch, Energy convers. Manage. 50, 2522-2526 (2009)
[11] Pan, Quan-Ke; Suganthan, P. N.; Tasgetiren, M. Fatih: A self-adaptive global best harmony search algorithm for continuous optimization problems, Appl. math. Comput. 216, 830-848 (2010) · Zbl 1189.65129 · doi:10.1016/j.amc.2010.01.088
[12] Bilal, Alatas: Chaotic harmony search algorithms, Appl. math. Comput. 216, 2687-2699 (2010) · Zbl 1193.65094 · doi:10.1016/j.amc.2010.03.114
[13] Li, L.; Chi, S. -C.; Lin, G.: Slope stability analysis using extremum principle by pan jiazheng and harmony search method, Rock soil mech. 28, 157-162 (2007)
[14] Omran, M. G. H.; Mahdavi, M.: Global-best harmony search, Appl. math. Comput. 198, 643-656 (2008) · Zbl 1146.90091 · doi:10.1016/j.amc.2007.09.004
[15] Fesanghary, M.; Mahdavi, M.; Minary-Jolandan, M.; Alizadeh, Y.: Hybridizing sequential quadratic programming with HS algorithm for engineering optimization, Comput. methods appl. Mech. engrg. 197, 3080-3091 (2008) · Zbl 1194.74243 · doi:10.1016/j.cma.2008.02.006
[16] Chakraborty, P.; Roy, G. G.; Das, S.; Jain, D.; Abraham, A.: An improved harmony search algorithm with differential mutation operator, Fund. inform. 95, 401-426 (2009) · Zbl 1209.68169 · doi:10.3233/FI-2009-157
[17] Erdal, F.; Saka, M. P.: Effect of beam spacing in the harmony search based optimum design of grillages, Asian J. Civil eng. (Building and housing) 9, 215-228 (2008)
[18] Gao, X. Z.; Wang, X.; Ovaska, S. J.: Modified harmony search methods for unimodal and multi-modal optimization, , 10-12 (2008)
[19] Li, Q.; Yang, S.; Ruan, Y.: A hybrid algorithm for optimizing multi-modal functions, Wuhan univ. J. nat. Sci. 11, 551-554 (2006) · Zbl 1100.90060 · doi:10.1007/BF02836663
[20] Geem, Z. W.: Particle-swarm harmony search for water network design, Eng. optim. 49, 297-311 (2009)
[21] K.-C. Lo, A HS-DLM hybrid searching algorithm for structural optimization, Masters thesis, National Central University, Taiwan (2008) (in Chinese).
[22] Wu, Bin; Qian, Cunhua; Ni, Weihong; Fan, Shuhai: The improvement of glowworm swarm optimization for continuous optimization problems, Expert syst. Appl. 39, 6335-6342 (2012) · Zbl 1268.90164
[23] Karaboga, D.; Basturk, B.: A powerful and efficient algorithm for numerical function optimization: artificial bee colony algorithm, J. global optim. 3, 9459-9471 (2007) · Zbl 1149.90186 · doi:10.1007/s10898-007-9149-x
[24] Karaboga, D.; Basturk, B.: On the performance of artificial bee colony algorithm, Appl. soft comput. 8, 687-697 (2008)
[25] Karaboga, D.; Bahriye, Akay: A comparative study of artificial bee colony algorithm, Appl. math. Comput. 214, 108-132 (2009) · Zbl 1169.65053 · doi:10.1016/j.amc.2009.03.090
[26] Zhao, Xiang; Yao, Yuan; Yan, Liping: Learning algorithm for multimodal optimization, Comput. math. Appl. 57, 2016-2021 (2009) · Zbl 1186.68402 · doi:10.1016/j.camwa.2008.10.008
[27] Heidari-Bateni, G.; Mcgillem, C. D.: A chaotic direct-sequence spread spectrum communication system, IEEE trans. Commun. 42, 1524-1527 (1994)
[28] Bilal, Alatas: Chaotic bee colony algorithms for global numerical optimization, Expert syst. Appl. 37, 5682-5687 (2010)
[29] Kennedy, J.; Eberhart, R. C.; Shi, Y.: Swarm intelligence, (2001)
[30] Fang, K. T.: The uniform design: application of number-theoretic methods in experimental design, Acta math. Appl. sin. 3, 363-372 (1980) · Zbl 0473.62067
[31] Fang, Kai-Tai; Qin, Hong: A note on construction of nearly uniform designs with large number of runs, Statist. probab. Lett. 61, 215-224 (2003) · Zbl 1038.62069 · doi:10.1016/S0167-7152(02)00357-7