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
745 2018

Al-Betar, M. A., Awadallah, M. A., Faris, H., Aljarah, I., & Hammouri, A. I. (2018). Natural selection methods for grey wolf optimizer. Expert Systems with Applications, 113, 481-498.

Citation /
Major :
Computer Science
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744 2018

Xu, W., Wang, R., & Yang, J. (2018). An improved league championship algorithm with free search and its application on production scheduling. Journal of Intelligent Manufacturing, 29(1), 165-174.

Citation /
Major :
Computer Science
DOWNLOAD LINK
743 2018

Wang, H., & Yi, J. H. (2018). An improved optimization method based on krill herd and artificial bee colony with information exchange. Memetic Computing, 10(2), 177-198.

Citation /
Major :
Computer Science
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742 2018

Bansal, J. C., Joshi, S. K., & Sharma, H. (2018). Modified global best artificial bee colony for constrained optimization problems. Computers & Electrical Engineering, 67, 365-382.

Citation /
Major :
Computer Science
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741 2018

Liu, S., Wu, H., Rahman, M. A., Lin, S. C. F., Wong, C. Y., Kwok, N., & Shi, H. (2018). Enhancement of low illumination images based on an optimal hyperbolic tangent profile. Computers & Electrical Engineering, 70, 538-550.

Citation /
Major :
Computer Science
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740 2018

Vommi, V. B., & Vemula, R. (2018). A very optimistic method of minimization (VOMMI) for unconstrained problems. Information Sciences, 454, 255-274.

Citation /
Major :
Computer Science
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739 2018

Shehab, M., Khader, A. T., & Laouchedi, M. (2018). A hybrid method based on cuckoo search algorithm for global optimization problems. Journal of Information and Communication Technology, 17(3), 469-491.

Citation /
Major :
Computer Science
DOWNLOAD LINK
738 2018

Nascimento, L. B. P., Pinto, V. P., & Amora, M. A. B. (2018). Harmony Search Algorithm with Adaptive Parameters to Optimize the Linear Quadratic Regulator Design. IEEE Latin America Transactions, 16(7), 1862-1869.

Citation /
Major :
Computer Science
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737 2018

Duman, S. (2018). A modified moth swarm algorithm based on an arithmetic crossover for constrained optimization and optimal power flow problems. IEEE Access, 6, 45394-45416.

Citation /
Major :
Computer Science
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736 2018

Bala, A., Ismail, I., Ibrahim, R., & Sait, S. M. (2018). Applications of metaheuristics in reservoir computing techniques: a review. IEEE Access, 6, 58012-58029.

Citation /
Major :
Computer Science
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735 2018

Li, C., Niu, Z., Song, Z., Li, B., Fan, J., & Liu, P. X. (2018). A double evolutionary learning moth-flame optimization for real-parameter global optimization problems. IEEE Access, 6, 76700-76727.

Citation /
Major :
Computer Science
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734 2018

Bansal, J. C., Gopal, A., & Nagar, A. K. (2018). Analysing convergence, consistency, and trajectory of artificial bee colony algorithm. IEEE Access, 6, 73593-73602.

Citation /
Major :
Computer Science
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733 2018

Gaidhane, P. J., & Nigam, M. J. (2018). A hybrid grey wolf optimizer and artificial bee colony algorithm for enhancing the performance of complex systems. Journal of computational science, 27, 284-302.

Citation /
Major :
Computer Science
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732 2018

Dinkar, S. K., & Deep, K. (2018). An efficient opposition based Lévy Flight Antlion optimizer for optimization problems. Journal of computational science, 29, 119-141.

Citation /
Major :
Computer Science
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731 2018

Shastri, A. S., & Kulkarni, A. J. (2018). Multi-cohort intelligence algorithm: an intra-and inter-group learning behaviour based socio-inspired optimisation methodology. International Journal of Parallel, Emergent and Distributed Systems, 33(6), 675-715.

Citation /
Major :
Computer Science
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730 2018

Abdi, Y., & Seyfari, Y. (2018). Search Manager: a framework for hybridizing different search strategies. International journal of advanced computer science and applications, 9, 525-540.

Citation /
Major :
Computer Science
729 2018

Gao, H., Li, J., & Diao, M. (2018). Direction finding of bistatic MIMO radar based on quantum-inspired grey wolf optimization in the impulse noise. EURASIP Journal on Advances in Signal Processing, 2018(1), 1-14.

Citation /
Major :
Computer Science
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728 2018

Sahib, M. A., Abdulnabi, A. R., & Mohammed, M. A. (2018). Improving bacterial foraging algorithm using non-uniform elimination-dispersal probability distribution. Alexandria engineering journal, 57(4), 3341-3349.

Citation /
Major :
Computer Science
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727 2018

Farnad, B., & Jafarian, A. (2018). A new nature-inspired hybrid algorithm with a penalty method to solve constrained problem. International Journal of Computational Methods, 15(08), 1850069.

Citation /
Major :
Computer Science
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726 2018

Farnad, B., Jafarian, A., & Baleanu, D. (2018). A new hybrid algorithm for continuous optimization problem. Applied Mathematical Modelling, 55, 652-673.

Citation /
Major :
Computer Science
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