[
1. Gosselin L, Tye-Gingras M, Mathieu-Potvin F. Review of utilization of genetic algorithms in heat transfer problems. International Journal of Heat and Mass Transfer. 2009; 52(9-10):2169-2188.10.1016/j.ijheatmasstransfer.2008.11.015
]Search in Google Scholar
[
2. Kot V. Solution of the classical Stefan problem: Neumann condition. Journal of Engineering Physics and Thermophysics. 2017; 90(4): 889-917.10.1007/s10891-017-1638-2
]Search in Google Scholar
[
3. Chen J, Yu W, Tian J, Chen L, Zhou Z. Image contrast enhancement using an artificial bee colony algorithm. Swarm and Evolutionary Computation. 2018; 38:287-294.10.1016/j.swevo.2017.09.002
]Search in Google Scholar
[
4. Zhao X, Xuan D, Zhao K, Li Z. Elman neural network using ant colony optimization algorithm for estimating of state of charge of lithium-ion battery. Journal of Energy Storage. 2020; 32:101789.10.1016/j.est.2020.101789
]Search in Google Scholar
[
5. Karaboga D, Gorkemli B, Ozturk C, Karaboga N. A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artificial Intelligence Review. 2014; 42:21-57.10.1007/s10462-012-9328-0
]Search in Google Scholar
[
6. Karaboga D. An idea based on honey bee swarm for numerical optimization. Technical Report. Kayseri/Türkiye: Erciyes University, Engineering Faculty, Computer Engineering Department; 2005. Report No.: TR-06.
]Search in Google Scholar
[
7. Karaboga D, Basturk B. On the performance of artificial bee colony (ABC) algorithm. Applied Soft Computing. 2008; 8(1):687-697.10.1016/j.asoc.2007.05.007
]Search in Google Scholar
[
8. Hetmaniok E, Słota D, Zielonka A. Artificial Bee Colo-ny Algorithm Used for Reconstructing the Heat Flux Density in the Solidification Process. In International Conference on Artificial Intel-ligence and Soft Computing; 2014; 363–372.10.1007/978-3-319-07176-3_32
]Search in Google Scholar
[
9. Hetmaniok E, Słota D, Zielonka A, Wituła R. Comparison of ABC and ACO Algorithms Applied for Solving the Inverse Heat Conduction Problem. In International Symposium on Swarm Intelligence and Differential Evolution; 2012; 249–257.10.1007/978-3-642-29353-5_29
]Search in Google Scholar
[
10. Hetmaniok E, Słota D, Zielonka A. Restoration of the cooling conditions in a three-dimensional continuous casting process using AI algorithms. Applied Mathematical Modelling. 2015; 39(16): 4794-4807.10.1016/j.apm.2015.03.056
]Search in Google Scholar
[
11. Zielonka A, Hetmaniok E, Słota D. Inverse alloy solidification problem including the material phenomenon solved by using the bee algorithm. International Communications in Heat and Mass Transfer. 2017; 87:295-301.10.1016/j.icheatmasstransfer.2017.07.014
]Search in Google Scholar
[
12. Grzymkowski R, Hetmaniok E, Słota D, Zielonka A. Application of the Ant Colony Optimization Algorithm in Solving the Inverse Stefan Problem. In Metal Forming; 2012; 1287-1290.
]Search in Google Scholar
[
13. Hetmaniok E, Słota D, Zielonka A. Application of the Swarm Intelligence Algorithm for Investigating the Inverse Continuous Casting Problem. Contemporary Challenges and Solutions in Applied Artificial Intelligence. 2013; 489: 157–162.10.1007/978-3-319-00651-2_21
]Search in Google Scholar
[
14. Matsevityi YM, Alekhina SV, Borukhov VT. Identification of the thermal conductivity coefficient for quasi-stationary two-dimensional heat conduction equations. Journal of Engineering Physics and Thermophysics. 2017; 90(6):1295-1301.10.1007/s10891-017-1686-7
]Search in Google Scholar
[
15. Tereshko V, Loengarov A. Collective decision-making in honey bee foraging dynamics. Computing and Information Systems. 2005; 9: 1-7.
]Search in Google Scholar
[
16. Colorni A, Dorigo M, Maniezzo V. Distributed Optimization by Ant Colonies. In Proceedings of the European Conference on Artificial Life; 1991; 134-142.
]Search in Google Scholar
[
17. Dorigo M, Maniezzo V, Colorni A. Ant system: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics). 1996; 26(1):29-41.10.1109/3477.484436
]Search in Google Scholar
[
18. Dorigo M, Di Caro G. Ant colony optimization: a new meta-heuristic. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99; 1999;1470-1477.
]Search in Google Scholar
[
19. Geuzaine C, Remacle JF. GMSH: a three-dimensional finite element mesh generator with built-in pre- and post-processing facilities. International Journal for Numerical Methods in Engineering. 2009; 79(11):1309-1331.10.1002/nme.2579
]Search in Google Scholar
[
20. Dyja R, Grosser A. Oblicznia równoległe w symulacji krzepnięcia wykorzystującej model pośredni narstania fazy stałej. Modelowanie Inżynierskie. 2015; 24(55):21-26.
]Search in Google Scholar
[
21. Dyja R, Gawronska E, Grosser A, Jeruszka P, Sczygiol N. Estimate the Impact of Different Heat Capacity Approximation Methods on the Numerical Results During Computer Simulation of Solidification. Engineering Letters. 2016; 24(2):237-245.
]Search in Google Scholar
[
22. Kodali HK, Ganapathysubramanian B. A computational framework to investigate charge transport in heterogeneous organic photovoltaic devices. Computer Methods in Applied Mechanics and Engineering. 2012; 247:113-129.
]Search in Google Scholar
[
23. Balay S, Gropp WD, McInnes LC, Smith BF. Efficient Management of Parallelism in Object-Oriented Numerical Software Libraries. In Arge E,BAM,LHP. Modern Software Tools for Scientific Computing. Boston. 1997;163–202.10.1007/978-1-4612-1986-6_8
]Search in Google Scholar
[
24. Dyja R. Comparison of Results from In-House Solidification Convection Model with Standard Benchmark. Acta Physica Polonica. 2021; 139(5):525-528.10.12693/APhysPolA.139.525
]Search in Google Scholar
, 