Czerniak, J.M., Dobrosielski, W.T., Filipowicz, I.: Comparing fuzzy numbers using de fuzzificators on ofn shapes. In: Prokopowicz, P., Czerniak, J.M., Mikolajewski, D., Apiecionek, L., Slezak, D. (eds.) Theory and Applications of Ordered Fuzzy Numbers. A Tribute to Professor Witold Kosinski, pp. 99–132. Studies in Fuzziness and Soft Computing, Springer International Publishing (2017).
DOI: https://doi.org/10.1007/978-3-319-59614-3_6
Czerniak, J.M., Zarzycki, H.: Artificial Acari Optimization as a new strategy for Global Optimization of Multimodal Functions. Journal of Computational Science (2017).
DOI: https://doi.org/10.1016/j.jocs.2017.05.028
Czerniak, J.M.: Zastosowania skierowanych liczb rozmytych w wybranych algorytmach optymalizacji rojowej (2019), Wydawnictwo Uniwersytetu Kazimierza Wielkiego w Bydgoszczy.
Das, S., Biswas, A., Dasgupta, S., Abraham, A.: Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications, pp. 23–55. Springer, Berlin, Heidelberg (2009).
DOI: https://doi.org/10.1007/978-3-642-01085-9_2
Galas, K.: Drive unit as a replacement for the platform. Studies and Materials in Applied Computer Science (ISSN 1689-6300) 12(1), 10–14 (2020).
Izuk, B., Piechowiak, M.: The impact of ant colony optimization parameters on the connections efficiency in networks. Studies and Materials in Applied Computer Science (ISSN 1689-6300) 12(2), 4–9 (2020).
Kosinski, W., Piasecki, W., Wilczynska-Sztyma, D.: On fuzzy rules and defuzzification functionals for Ordered Fuzzy Numbers. In: Proc. of AI-Meth’2009 Conference, November 2009, pp. 161–178. AI-METH Series, Gliwice (2009).
Kosinski, W., Wilczynska-Sztyma, D.: Defuzzification and Implication Within Ordered Fuzzy Numbers. In: Fuzzy Systems (FUZZ), 2010 IEEE International Conference on Computational Intelligence. pp. 1–7. IEEE (2010).
DOI: https://doi.org/10.1109/FUZZY.2010.5584226
Kosinski, W.: On Defuzzyfication of Ordered Fuzzy Numbers. In: Artificial Intelligence and Soft Computing - ICAISC 2004, Lecture Notes in Computer Science, vol. 3070, pp. 326–331. Springer Berlin Heidelberg (2004).
DOI: https://doi.org/10.1007/978-3-540-24844-6_46
Kwasnicka, H.S., Markowska-Kaczmar, U., Kwasnicka, H.: Metody inspirowane natura w zastosowaniach (2011)
Kwasnicka, H.S.: Multi objective particle swarm optimization using fuzzy logic (2011)
Lukowski, J.: Logical description of a combinatorial system by the binary representation method. Studies and Materials in Applied Computer Science (ISSN 1689-6300) 11(1), 10–12 (2019)..
Meng, X., Liu, Y., Gao, X., Zhang, H.: A New Bio-inspired Algorithm: Chicken Swarm Optimization. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds.) Advances in Swarm Intelligence. pp. 86–94. Springer International Publishing, Cham (2014)).
DOI: https://doi.org/10.1007/978-3-319-11857-4_10
Pham, D.T., Negm, M., Otri, S.: Using the bees algorithm to solve a stochastic optimization problem. 4th International Virtual Conference on Intelligent Production Machines and Systems (IPROMS) pp. 454–461 (Whittles, Dunbeath, Scotland, 2008).
Polberg, S., Paprzycki, M., Ganzha, M.: Developing intelligent bots for the diplomacy game. M. Ganzha, et.al. (eds.), Proceedings of the 2011 Federated Conference on Computer Science and Information Systems, IEEE CS Pres pp. 589–596 (Los Alamitos, CA, 2011).
Wilczynska-Sztyma, D., Wielki, K.: Direction of Research into Methods of Defuzzification for Ordered Fuzzy Numbers. XII International PhD Workshop OWD 2010, 23–26 October 2010 (07 2019).
Zadeh, L.: Fuzzy sets. Information and Control 8(3), 338–353 (1965), https://www.sciencedirect.com/science/article/pii/S001999586590241X.
DOI: https://doi.org/10.1016/S0019-9958(65)90241-X