Publications

Publications

The Harmony Search algorithm (HSA) publicatons found in Web of Science are applied in about 25 major fields (e.g., civil engineering, computer science, industrial engineering, business, economy, art).

Firstly,
they can be divided into whether the HSA was cited only (Citation) or was applied (Application).
Second,
(Application) publications can be divided into whether the Original HSA was used (HS) or modified HSA was used to improve the optimization performance (Variants of HS, VoHS).
Third,
(VoHS) publications can be divided into
whether it has one objective function (Single) or two or more objective function (Multi).

1) (Single) publications were classified as HS Operator, Parameter, Population-based and Hybrid.
· HS Operator : Papers that transform operators such as HMC and PA
· Parameter : Papers that used the modified equations for determining the values of HMCR, PAR, and BW
· Population-based : Papers in which HM divided into several groups (parallel calculation, solution exchange, etc.)
· Hybrid : Papers optimized by using other optimization algorithm’s operators are combined to improve search ability

2) (Multi) publications were classified as Non-Pareto or Pareto-based.
· Non-Pareto : Papers that select the optimal solutions through weighting method, etc.
· Pareto-based : Papers that select the optimal solutions through Pareto model
No. Year Journal
Information
Major DOWNLOAD
785 2013

Poursalehi, N., Zolfaghari, A., & Minuchehr, A. (2013). PWR loading pattern optimization using Harmony Search algorithm. Annals of Nuclear Energy, 53, 288-298.

HS / /
Major :
Civil Engineering (Energy)
DOWNLOAD LINK
784 2013

Aghaie, M., Nazari, T., Zolfaghari, A., Minuchehr, A., & Shirani, A. (2013). Investigation of PWR core optimization using harmony search algorithms. Annals of Nuclear Energy, 57, 1-15.

Application / HS /
Major :
Civil Engineering (Energy)
DOWNLOAD LINK
783 2013

De Corte, A., & Sörensen, K. (2013). Optimisation of gravity-fed water distribution network design: A critical review. European Journal of Operational Research, 228(1), 1-10.

Application / HS / /
Major :
Civil Engineering (Water Resources)
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782 2013

Yoon, S., Jeong, C., & Lee, T. (2013). Application of harmony search to design storm estimation from probability distribution models. Journal of Applied Mathematics, 2013.

Application / HS /
Major :
Civil Engineering (Water Resources)
DOWNLOAD LINK
781 2013

Ayvaz, M. T., & Elçi, A. (2013). A groundwater management tool for solving the pumping cost minimization problem for the Tahtali watershed (Izmir-Turkey) using hybrid HS-Solver optimization algorithm. Journal of Hydrology, 478, 63-76.

Application / HS / /
Major :
Civil Engineering (Water Resources)
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780 2018

Cheraghalipour, A., Hajiaghaei-Keshteli, M., & Paydar, M. M. (2018). Tree Growth Algorithm (TGA): A novel approach for solving optimization problems. Engineering Applications of Artificial Intelligence, 72, 393-414.

Citation /
Major :
Computer Science
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779 2018

Duc, L. A., Li, K., Nguyen, T. T., Yen, V. M., & Truong, T. K. (2018). A new effective operator for the hybrid algorithm for solving global optimisation problems. International Journal of Systems Science, 49(5), 1088-1102.

Citation /
Major :
Computer Science
DOWNLOAD LINK
778 2018

Zhuoran, Z., Changqiang, H., Hanqiao, H., Shangqin, T., & Kangsheng, D. (2018). An optimization method: hummingbirds optimization algorithm. Journal of Systems Engineering and Electronics, 29(2), 386-404.

Citation /
Major :
Computer Science
DOWNLOAD LINK
777 2018

Yassine, A. A., Kingsford, W., Xu, Y., Cassidy, J., Lilge, L., & Betz, V. (2018). Automatic interstitial photodynamic therapy planning via convex optimization. Biomedical optics express, 9(2), 898-920.

Citation /
Major :
Computer Science
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776 2018

Mitikiri, P., Jana, G., Sural, S., & Chattaraj, P. K. (2018). A machine learning technique toward generating minimum energy structures of small boron clusters.

Citation /
Major :
Computer Science
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775 2018

Sur, C., & Shukla, A. (2018). Discrete bacteria foraging optimization algorithm for graph based problems–a transition from continuous to discrete. Journal of Experimental & Theoretical Artificial Intelligence, 30(2), 345-365.

Citation /
Major :
Computer Science
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774 2018

Abdel-Basset, M., Hessin, A. N., & Abdel-Fatah, L. (2018). A comprehensive study of cuckoo-inspired algorithms. Neural Computing and Applications, 29(2), 345-361.

Citation /
Major :
Computer Science
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773 2018

Nabaei, A., Hamian, M., Parsaei, M. R., Safdari, R., Samad-Soltani, T., Zarrabi, H., & Ghassemi, A. (2018). Topologies and performance of intelligent algorithms: a comprehensive review. Artificial Intelligence Review, 49(1), 79-103.

Citation /
Major :
Computer Science
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772 2018

Osaba, E., Carballedo, R., Diaz, F., Onieva, E., Masegosa, A. D., & Perallos, A. (2018). Good practice proposal for the implementation, presentation, and comparison of metaheuristics for solving routing problems. Neurocomputing, 271, 2-8.

Citation /
Major :
Computer Science
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771 2018

García, J., Crawford, B., Soto, R., Castro, C., & Paredes, F. (2018). A k-means binarization framework applied to multidimensional knapsack problem. Applied Intelligence, 48(2), 357-380.

Citation /
Major :
Computer Science
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770 2018

Fattahi, E., Bidar, M., & Kanan, H. R. (2018). Focus group: an optimization algorithm inspired by human behavior. International Journal of Computational Intelligence and Applications, 17(01), 1850002.

Citation /
Major :
Computer Science
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769 2018

Borkar, P., & Sarode, M. V. (2018). Modality of teaching learning based optimization algorithm to reduce the consistency ratio of the pair-wise comparison matrix in analytical hierarchy processing. Evolving Systems, 9(2), 169-180.

Citation /
Major :
Computer Science
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768 2018

Ghanem, W. A., & Jantan, A. (2018). Hybridizing artificial bee colony with monarch butterfly optimization for numerical optimization problems. Neural Computing and Applications, 30(1), 163-181.

Citation /
Major :
Computer Science
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767 2018

Nayak, J., Naik, B., Behera, H. S., & Abraham, A. (2018). Elitist teaching–learning-based optimization (ETLBO) with higher-order Jordan Pi-sigma neural network: a comparative performance analysis. Neural Computing and Applications, 30(5), 1445-1468.

Citation /
Major :
Computer Science
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766 2018

Liu, W., Luo, N., Pan, G., & Ouyang, A. (2018). Chaos particle swarm optimization algorithm for optimization problems. International Journal of Pattern Recognition and Artificial Intelligence, 32(11), 1859019.

Citation /
Major :
Computer Science
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