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In [[computer science]] and [[operations research]], '''harmony search''' (HS) is a phenomenon-mimicking algorithm (also known as [[metaheuristic]] [[algorithm]], [[soft computing]] algorithm or [[evolutionary algorithm]]) inspired by the improvisation process of musicians proposed by [[Zong Woo Geem]] in 2001. In the HS algorithm, each musician (= decision variable) plays (= generates) a note (= a value) for finding a best harmony (= global optimum) all together. Proponents claim the following merits:{{citation needed|date=April 2013}}
 
* HS does not require differential gradients, thus it can consider discontinuous functions as well as continuous functions.
* HS can handle [http://sim.sagepub.com/cgi/content/abstract/76/2/60 discrete variables] as well as [http://dx.doi.org/10.1016/j.cma.2004.09.007 continuous variables].
* HS does not require initial value setting for the variables.
* HS is free from divergence.
* HS may escape local optima.
* HS may overcome the drawback of GA's [[Genetic_algorithms#The building_block_hypothesis|building block theory]] which works well only if the relationship among variables in a chromosome is carefully considered. If neighbor variables in a chromosome have weaker relationship than remote variables, building block theory may not work well because of crossover operation. However, HS explicitly considers the relationship using [http://dx.doi.org/10.1007/11892960_11 ensemble operation].
* HS has a novel [http://dx.doi.org/10.1016/j.amc.2007.09.049 stochastic derivative] applied to discrete variables, which uses musician's experiences as a searching direction.
* Certain HS variants do not require algorithm parameters such as HMCR and PAR, thus novice users can easily use the algorithm.
 
==Basic harmony search algorithm==
 
Harmony search tries to find a vector <math>\mathbf{x}</math> which optimizes (minimizes or maximizes) a certain objective function.
 
The algorithm has the following steps:
 
Step 1: Generate random vectors (<math>\mathbf{x}^1, \ldots, \mathbf{x}^{hms}</math>) as many as <math>hms</math> (harmony memory size), then store them in harmony memory (HM).
:<math>
\mathbf{HM} =
\begin{bmatrix}
x^1_1 & \cdots & x^1_n & | & f(\mathbf{x}^1)\\
\vdots & \ddots & \vdots & | & \vdots\\
x^{hms}_1 & \cdots & x^{hms}_n & | & f(\mathbf{x}^{hms})\\
\end{bmatrix}.
</math>
 
Step 2: Generate a new vector <math>\mathbf{x}'</math>. For each component <math>x^{'}_{i}</math>,
 
* with probability <math>hmcr</math> (harmony memory considering rate; 0 ≤ <math>hmcr</math> ≤ 1), pick the stored value from HM: <math>x^{'}_{i} \leftarrow x^{int(u(0, 1)*hms)+1}_i</math>
* with probability <math>1-hmcr</math>, pick a random value within the allowed range.
 
Step 3: Perform additional work if the value in Step 2 came from HM.
 
* with probability <math>par</math> (pitch adjusting rate; 0 ≤ <math>par</math> ≤ 1), change <math>x^{'}_{i}</math> by a small amount: <math>x^{'}_{i} \leftarrow x^{'}_{i} + \delta</math> or <math>x^{'}_{i} \leftarrow x^{'}_{i} - \delta</math> for discrete variable; or <math>x^{'}_{i} \leftarrow x^{'}_{i} + fw \cdot u(-1, 1)</math> for continuous variable.
* with probability <math>1-par</math>, do nothing.
 
Step 4: If <math>\mathbf{x}^{'}</math> is better than the worst vector <math>\mathbf{x}^{Worst}</math> in HM, replace <math>\mathbf{x}^{Worst}</math> with <math>\mathbf{x}'</math>.
 
Step 5: Repeat from Step 2 to Step 4 until termination criterion (e.g. maximum iterations) is satisfied.
 
The parameters of the algorithm are
* <math>hms</math> = the size of the harmony memory. It generally varies from 1 to 100. (typical value = 30)
* <math>hmcr</math> = the rate of choosing a value from the harmony memory. It generally varies from 0.7 to 0.99. (typical value = 0.9)
* <math>par</math> = the rate of choosing a neighboring value. It generally varies from 0.1 to 0.5. (typical value = 0.3)
* <math>\delta</math> = the amount between two neighboring values in discrete candidate set.
* <math>fw</math> (fret width, formerly bandwidth) = the amount of maximum change in pitch adjustment. This can be (0.01 × allowed range) to (0.001 × allowed range).
 
It is possible to vary the parameter values as the search progresses, which gives an effect similar to [[simulated annealing]].
 
Parameter-setting-free researches have been also performed. In the researches, algorithm users do not need tedious parameter setting process.
 
==Other related algorithms==
Harmony search lies in the fields of:
* [[Evolutionary computation|Evolutionary computing]]
**[[Metaheuristic]]s
***[[Stochastic optimization]]
****[[Optimization (mathematics)|Optimization]]
 
Other evolutionary computing methods include:
*[[Evolutionary algorithms]], including:
**[[Genetic algorithm]]s
**[[Genetic programming]]
*[[Swarm Intelligence|Swarm algorithms]], including:
** [[Ant colony optimization]]
** [[Particle swarm optimization]]
** [[Intelligent Water Drops]]
 
Other metaheuristic methods include:
* [[Simulated annealing]]
* [[Tabu search]]
 
Other stochastic methods include:
* [[Cross-entropy method]]
 
==Criticism==
In 2010, Dennis Weyland, a PhD student at the [[Dalle Molle Institute for Artificial Intelligence Research]] in Switzerland published an article titled "A Rigorous Analysis of the Harmony Search Algorithm: How the Research Community can be Misled by a “Novel” Methodology" in the ''[[International Journal of Applied Metaheuristic Computing]]'' (IJAMC),<ref>{{cite journal|last=Weyland|first=Dennis|title=A Rigorous Analysis of the Harmony Search Algorithm: How the Research Community can be Misled by a "Novel" Methodology|journal=[[International Journal of Applied Metaheuristic Computing]]|volume=1|issue=2|year=2010|pages=50–60|doi=10.4018/jamc.2010040104}}</ref> stating that:
<blockquote>
It turns out that ''Harmony Search'' is a special case of ''[[Evolution Strategies]]''. We give compelling evidence for the thesis that research in Harmony Search, although undoubtedly conducted with the best of intentions, is fundamentally misguided, marred by a preoccupation with retracing paths already well traveled, and we conclude that future research effort could better be devoted to more promising areas.  
</blockquote>
A rebuttal was published by Geem in a later issue of the same journal,<ref>{{cite journal|last=Geem|first=Zong Woo|title=Research Commentary: Survival of the Fittest Algorithm or the Novelest Algorithm?|journal=[[International Journal of Applied Metaheuristic Computing]]|volume=1|issue=4|year=2010|pages=75–79|doi=10.4018/jamc.2010100105}}</ref> [https://sites.google.com/a/hydroteq.com/www/criticism_hs.pdf (updated manuscript)] but Kenneth Sörensen, professor of [[operations research]] at [[Antwerp University]], called it "less than fully convincing".<ref>{{cite journal|first=Kenneth|last=Sörensen|title=Metaheuristics—the metaphor exposed|journal=[[International Transactions in Operational Research]]|doi=10.1111/itor.12001}}</ref>
 
Independent of the work of Weyland, Miriam Padberg has shown in 2011 that for binary optimization problems the Harmony Search algorithm is equivalent to a certain evolutionary algorithm.<ref>Padberg, Miriam (2012). "Harmony Search Algorithms for binary optimization problems". Operations Research Proceedings 2012: 343–348.</ref> In fact, the reasoning is similar to that used in the work of Weyland, but this time explicitly stated in a rigorous mathematical way.
 
== Notes ==
{{reflist|2}}
 
==References==
 
===General information===
 
*Algorithm Website: [http://www.hydroteq.com Harmony Search Algorithm]
* Book 1 [http://www.springer.com/engineering/book/978-3-642-00184-0 Music-Inspired Harmony Search Algorithm, Springer 2009]
* Book 2 [http://www.springer.com/engineering/book/978-3-642-04316-1 Recent Advances in Harmony Search Algorithm, Springer 2010]
* Book 3 [http://www.springer.com/engineering/book/978-3-642-03449-7 Harmony Search Algorithms for Structural Design Optimization, Springer 2009]
* Book 4 [http://www.amazon.com/gp/product/3838305833 Optimal Design of Water Distribution Networks Using Harmony Search, LAP 2009]
* Book 5 [http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470582464.html Engineering Optimization: An Introduction with Metaheuristic Applications, Wiley 2010]
* Book 6 [http://www.cleveralgorithms.com/ Clever Algorithms: Nature-Inspired Programming Recipes, Lulu.com 2011]
 
===Theory of harmony search===
 
*Original Harmony Search: Geem ZW, Kim JH, and Loganathan GV, [http://sim.sagepub.com/cgi/content/abstract/76/2/60 A New Heuristic Optimization Algorithm: Harmony Search], Simulation, 2001.
*Stochastic Partial Derivative: Geem ZW, [http://dx.doi.org/10.1016/j.amc.2007.09.049 Novel Derivative of Harmony Search Algorithm for Discrete Design Variables], Applied Mathematics and Computation, 2008.
*Ensembled Harmony Search: Geem ZW, [http://www.springerlink.com/content/b382536117777v22/ Improved Harmony Search from Ensemble of Music Players], Lecture Notes in Artificial Intelligence, 2006.
*Continuous Harmony Search: Lee KS and Geem ZW, [http://dx.doi.org/10.1016/j.cma.2004.09.007 A New Meta-Heuristic Algorithm for Continuous Engineering Optimization: Harmony Search Theory and Practice], Computer Methods in Applied Mechanics and Engineering, 2005.
* Exploratory Power of Harmony Search: Das S, Mukhopadhyay A, Roy A, Abraham A, Panigrahi BK, [http://dx.doi.org/10.1109/TSMCB.2010.2046035 Exploratory Power of the Harmony Search Algorithm: Analysis and Improvements for Global Numerical Optimization], IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 41(1), 2011.
*Improved Harmony Search: Mahdavi M, Fesanghary M, and Damangir E, [http://dx.doi.org/10.1016/j.amc.2006.11.033 An Improved Harmony Search Algorithm for Solving Optimization Problems], Applied Mathematics and Computation, 2007.
*Particle-Swarm Harmony Search: Omran MGH and Mahdavi M, [http://dx.doi.org/10.1016/j.amc.2007.09.004 Global-Best Harmony Search], Applied Mathematics and Computation, 2008.
*Hybrid Harmony Search: Fesanghary M, Mahdavi M, Minary-Jolandan M, and Alizadeh Y, [http://dx.doi.org/10.1016/j.cma.2008.02.006 Hybridizing Harmony Search Algorithm with Sequential Quadratic Programming for Engineering Optimization Problems], Computer Methods in Applied Mechanics and Engineering, 2008.
*Parameter-Setting-Free Harmony Search: Geem ZW and Sim K-B, [http://dx.doi.org/10.1016/j.amc.2010.09.049 Parameter-Setting-Free Harmony Search Algorithm], Applied Mathematics and Computation, 2010.
*Multiobjective Harmony Search Algorithm Proposals: Juan Ricart, Germán Hüttemann, Joaquín Lima, Benjamín Barán. [http://dx.doi.org/10.1016/j.entcs.2011.11.025 Multiobjective Harmony Search Algorithm Proposals], Electronic Notes in Theoretical Computer Science, 2011.
* Hybrid Harmony Search: HS-BFGS algorithm : Karahan H, Gurarslan G and Geem ZW, [doi:http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000608 "Parameter Estimation of the nonlinear Muskingum flood routing model using a hybrid harmony search algorithm", Journal of Hydrologic Engineering, {{doi|10.1061/(ASCE)HE.1943-5584.0000608}}, 2012.
*Generalised Adaptive Harmony Search: Jaco Fourie, Richard Green, and Zong Woo Geem, [http://www.hindawi.com/journals/jam/2013/380985/cta/ Generalised Adaptive Harmony Search: A Comparative Analysis of Modern Harmony Search], Journal of Applied Mathematics, vol. 2013, Article ID 380985, 13 pages, 2013. doi:10.1155/2013/380985
 
===Applications in computer science===
 
*Music Composition: Geem, Z. W. and Choi, J. Y. [http://www.springerlink.com/content/8395xp88473826p0/?p=9a58d87e926f47fc9782388b495670a8&pi=3 Music Composition Using Harmony Search Algorithm], Lecture Notes in Computer Science, 2007.
*Tetris Agent Optimization: Romero, V., Tomes, L., Yusiong, J., [http://ijcsi.org/papers/IJCSI-8-1-22-31.pdf Harmonetris: Tetris Agent Optimization Using Harmony Search Algorithm], International Journal of Computer Science Issues, 2011.
*Sudoku Puzzle: Geem, Z. W. [http://www.springerlink.com/content/488571w6036764v0/?p=336060128e684defa2d88b3522bdbe27&pi=0 Harmony Search Algorithm for Solving Sudoku], Lecture Notes in Artificial Intelligence, 2007.
*Tour Planning: Geem, Z. W., Tseng, C. -L., and Park, Y. [http://www.springerlink.com/content/6jadggrn5v7bvtye/ Harmony Search for Generalized Orienteering Problem: Best Touring in China], Lecture Notes in Computer Science, 2005.
*Visual Tracking: J. Fourie, S. Mills and R. Green [http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4762068 Visual tracking using the harmony search algorithm], Image and Vision Computing New Zealand, 2008. 23rd International Conference
*Visual Tracking: Jaco Fourie, Steven Mills, Richard Green, [http://www.sciencedirect.com/science/article/B6V09-506W6M2-3/2/ab66f3c49ca2ebc18600db52b421d9d5 Harmony Filter: A Robust Visual Tracking System Using the Improved Harmony Search Algorithm], Image and Vision Computing (2010), {{doi|10.1016/j.imavis.2010.05.006}}
*Visual Correspondence: J. Fourie, S. Mills and R. Green [http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=5378431&isnumber=5378349 Directed correspondence search: Finding feature correspondences in images using the Harmony Search algorithm], Image and Vision Computing New Zealand, 23-25 Nov. 2009. 24th International Conference
*Image Deconvolution: J. Fourie, S. Mills and R. Green [http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5685093 Counterpoint Harmony Search: An accurate algorithm for the blind deconvolution of binary images], Audio Language and Image Processing (ICALIP), 2010 International Conference on, Shanghai, China
*Capacitated clustering 1: I. Landa-Torres, S. Gil-Lopez, S. Salcedo-Sanz, J. Del Ser, J. A. Portilla-Figueras, [http://www.sciencedirect.com/science/article/pii/S0957417411015430 A Novel Grouping Harmony Search Algorithm for the Multiple-Type Access Node Location Problem], Expert Systems with Applications, vol. 39, no. 5, pp.&nbsp;5262–5270, April 2012.
*Capacitated clustering 2: I. Landa-Torres, J. Del Ser, S. Salcedo-Sanz, S. Gil-Lopez, J.A. Portilla-Figueras, O. Alonso-Garrido, [http://www.sciencedirect.com/science/article/pii/S0305054811003194 A comparative study of two hybrid grouping evolutionary techniques for the capacitated P-median problem], Computers and Operations Research, vol. 39, no. 9, pp.&nbsp;2214–2222, September 2012.
*Design of radar codes: S. Gil-Lopez, J. Del Ser, S. Salcedo-Sanz, A. M. Perez-Bellido, J. M. Cabero and J. A. Portilla-Figueras, [http://www.sciencedirect.com/science/article/pii/S0957417412005866 A Hybrid Harmony Search Algorithm for the Spread Spectrum Radar Polyphase Codes Design Problem], Expert Systems with Applications, Volume 39, Issue 12, pp.&nbsp;11089–-11093, September 2012.
*Dynamic Spectrum Allocation: J. Del Ser, M. Matinmikko, S. Gil-Lopez and M. Mustonen, [http://www.sciencedirect.com/science/article/pii/S1568494611003942 Centralized and Distributed Spectrum Channel Assignment in Cognitive Wireless Networks: A Harmony Search Approach], Applied Soft Computing, vol. 12, no. 2, pp.&nbsp;921–930, February 2012.
*Power and subcarrier allocation in OFDMA systems: J. Del Ser, M. N. Bilbao, S. Gil-Lopez, M. Matinmikko, S. Salcedo-Sanz, [http://www.sciencedirect.com/science/article/pii/S0952197611000297 Iterative Power and Subcarrier Allocation in Rate-Constrained OFDMA Downlink Systems based on Harmony Search Heuristics], Elsevier Engineering Applications of Artificial Intelligence, Vol. 24, N. 5, pp.&nbsp;748–756, August 2011.
*Efficient design of open Wifi networks: I. Landa-Torres, S. Gil-Lopez, J. Del Ser, S. Salcedo-Sanz, D. Manjarres, J. A. Portilla-Figueras, [http://www.sciencedirect.com/science/article/pii/S0952197612001261 Efficient Citywide Planning of Open WiFi Access Networks using Novel Grouping Harmony Search Heuristics], accepted for its publication in Engineering Applications of Artificial Intelligence, May 2012.
*Single-objective localization: D. Manjarres, J. Del Ser, S. Gil-Lopez, M. Vecchio, I. Landa-Torres, R. Lopez-Valcarce, A Novel Heuristic Approach for Distance- and Connectivity-based Multihop Node Localization in Wireless Sensor Networks, Springer Soft Computing, accepted, June 2012.
*Bi-objective localization: D. Manjarres, J. Del Ser, S. Gil-Lopez, M. Vecchio, I. Landa-Torres, S. Salcedo-Sanz, R. Lopez-Valcarce,[http://www.sciencedirect.com/science/article/pii/S0952197612001455 On the Design of a Novel Two-Objective Harmony Search Approach for Distance- and Connectivity-based Node Localization in Wireless Sensor Networks], Engineering Applications of Artificial Intelligence, in press, June 2012.
 
===Applications in engineering===
 
*Fuzzy Data Clustering: Malaki, M.,Pourbaghery, JA, A Abolhassani, H. A combinatory approach to fuzzy clustering with harmony search and its applications to space shuttle data, Proceedings of the SCIS & ISIS,17–21,2008.
*Structural Design: Lee, K. S. and Geem, Z. W. [http://dx.doi.org/10.1016/j.compstruc.2004.01.002 A New Structural Optimization Method Based on the Harmony Search Algorithm], Computers & Structures, 2004.
*Structural Design: Saka, M. P. [http://dx.doi.org/10.1260/136943307783571445 Optimum Geometry Design of Geodesic Domes Using Harmony Search Algorithm], Advances in Structural Engineering, 2007.
*Water Network Design: Geem, Z. W. [http://dx.doi.org/10.1080/03052150500467430 Optimal Cost Design of Water Distribution Networks using Harmony Search], Engineering Optimization, 2006.
*Vehicle Routing: Geem, Z. W., Lee, K. S., and Park, Y. [http://www.doaj.org/doaj?func=abstract&id=175458&toc=y Application of Harmony Search to Vehicle Routing], American Journal of Applied Sciences, 2005.
*Ground Water Modeling: Ayvaz, M. T. [http://dx.doi.org/10.1016/j.advwatres.2007.05.009 Simultaneous Determination of Aquifer Parameters and Zone Structures with Fuzzy C-Means Clustering and Meta-Heuristic Harmony Search Algorithm], Advances in Water Resources, 2007.
*Soil Stability Analysis: Cheng, Y. M., Li, L., Lansivaara, T., Chi, S. C. and Sun, Y. J. [http://dx.doi.org/10.1080/03052150701618153 An Improved Harmony Search Minimization Algorithm Using Different Slip Surface Generation Methods for Slope Stability Analysis], Engineering Optimization, 2008.
*Energy System Dispatch: Vasebi, A., Fesanghary, M., and Bathaeea, S.M.T. [http://dx.doi.org/10.1016/j.ijepes.2007.06.006 Combined Heat and Power Economic Dispatch by Harmony Search Algorithm], International Journal of Electrical Power & Energy Systems, 2007.
*Offshore Structure Mooring: Ryu, S., Duggal, A.S., Heyl, C. N., and Geem, Z. W. [http://store.asme.org/product.asp?catalog%5Fname=Conference+Papers&category%5Fname=&product%5Fid=OMAE2007%2D29334 Mooring Cost Optimization via Harmony Search], Proceedings of the 26th International Conference on Offshore Mechanics and Arctic Engineering (OMAE 2007), ASME, San Diego, CA, USA, June 10–15, 2007.
*Hydrologic Parameter Calibration: Kim, J. H., Geem, Z. W., and Kim, E. S. [http://www.blackwell-synergy.com/doi/abs/10.1111/j.1752-1688.2001.tb03627.x Parameter Estimation of the Nonlinear Muskingum Model using Harmony Search], Journal of the American Water Resources Association, 2001.
* Hydrologic Parameter Calibration: Karahan, H, Gurarslan, G. and Geem, Z.W.[doi:http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000608 "Parameter Estimation of the nonlinear Muskingum flood routing model using a hybrid harmony search algorithm", Journal of Hydrologic Engineering, {{doi|10.1061/(ASCE)HE.1943-5584.0000608}}, 2012.
*Satellite Heat Pipe Design: Geem, Z. W. and Hwangbo, H. [http://www.hydroteq.com/c_2006_ukc_ast.pdf Application of Harmony Search to Multi-Objective Optimization for Satellite Heat Pipe Design], Proceedings of US-Korea Conference on Science, Technology, & Entrepreneurship (UKC 2006), CD-ROM, Teaneck, NJ, USA, Aug. 10-13 2006.
*Dam Scheduling: Geem, Z. W. [http://www.springerlink.com/content/x1q6618054866162/?p=3fb93efd6f4a460ea92a62a59fce6c3e&pi=38 Optimal Scheduling of Multiple Dam System Using Harmony Search Algorithm], Lecture Notes in Computer Science, 2007.
*Ecological Conservation: Geem, Z. W. and Williams, J. C. [http://www.naun.org/journals/energyenvironment/ee-26.pdf Ecological Optimization Using Harmony Search], Proceedings of American Conference on Applied Mathematics, Harvard University, Cambridge, MA, USA, March 24–26, 2008.
*Heat exchanger design: Fesanghary, M., Damangir, E. and Soleimani, I. [http://dx.doi.org/10.1016/j.applthermaleng.2008.05.018 Design optimization of shell and tube heat exchangers using global sensitivity analysis and harmony search], Applied Thermal Engineering, In press.
*Heat exchanger design: Doodman, A., Fesanghary, M. and Hosseini, R. [http://dx.doi.org/10.1016/j.apenergy.2008.08.021 A robust stochastic approach for design optimization of air cooled heat exchangers], Applied Energy, In press.
*Heat exchanger network design: Khorasani, R.M., Fesanghary, M. [http://dx.doi.org/10.1016/j.compchemeng.2008.12.004 A novel approach for synthesis of cost-optimal heat exchanger networks], Computers and Chemical Engineering, In press.
*Face milling: Zarei, O., Fesanghary, M., Farshi, B.,  Jalili Saffar, R. and Razfar, M.R.  [http://dx.doi.org/10.1016/j.jmatprotec.2008.05.029 Optimization of multi-pass face-milling via harmony search algorithm], Journal of Materials Processing Technology, In press.
*Document Clustering:, Mahdavi., M., Chehreghania, H., Abolhassania, H., Forsati, R. [http://dx.doi.org/10.1016/j.amc.2007.12.058 Novel meta-heuristic algorithms for document clustering], AMC Journal
*Multicast Routing: Forsat, R., Haghighat, M., Mahdavi, M.,[http://dx.doi.org/10.1016/j.comcom.2008.03.019 Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing], Computer Communications, Elsevier
*AYVAZ, M.T. and GENÇ, Ö., Optimal estimation of Manning’s roughness in open channel flows using a linked simulation-optimization model, BALWOIS 2012, International Conference on Water, Climate and Environment, May 28 - June 2, 2012, Ohrid, Madeconia.
*Poursalehi, N., Zolfaghari,A., Minuchehr, A., PWR loading pattern optimization using Harmony Search algorithm, Ann. Nucl. Energy, 2013, Vol. 53, pp. 288-298. [http://www.sciencedirect.com/science/article/pii/S0306454912003192]
 
===Applications in economics===
 
*I. Landa-Torres, E. G. Ortiz-Garcia, S. Salcedo-Sanz, M. J. Segovia, S. Gil-Lopez, M. Miranda, J. M. Leiva-Murillo, J. Del Ser, [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6200298&contentType=Early+Access+Articles&sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A5418892%29%26rowsPerPage%3D50 Evaluating the Internationalization Success of Companies using a Hybrid Grouping Harmony Search - Extreme Learning Machine Approach], IEEE Journal on Selected Topics in Signal Processing, Vol. PP., N. 99 (early access), May 2012.
 
==Source codes==
* Improved Harmony Search (MATLAB)  [https://sites.google.com/site/fesangharyweb/downloads]
* Hybrid HS-SQP (Visual C++) [https://sites.google.com/site/fesangharyweb/downloads]
* Multiobjective Harmony Search (C#) [https://sites.google.com/site/fesangharyweb/downloads]
* Other HS Variants [http://sites.google.com/a/hydroteq.com/www/]
* Multiobjective Harmony Search Algorithm Proposals (C++) [https://sites.google.com/site/multiobjectivehs/]
* pyHarmonySearch (Python) [https://github.com/gfairchild/pyHarmonySearch]
 
{{Optimization algorithms}}
 
[[Category:Optimization algorithms and methods]]
[[Category:Combinatorial optimization]]
[[Category:Evolutionary algorithms]]

Revision as of 16:29, 4 March 2014

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