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Τελευταίες Υποβολές

 61-75 από 891 αποτελέσματα
61 V. Markantonakis, A. Doko, I. Papamichail, M. Papageorgiou, K. Schrab, M. Neubauer, and R. Protzmann, “Traffic control algorithms for mixed vehicle traffic – A simulation-based investigation,” in 23rd EURO Working Group on Transportation Meeting, EWGT 2020, vol. 52, pp. 356-363, Jan. 2021, doi: 10.1016/j.trpro.2021.01.042.2022-06-02
62 C. H. Skiadas, Y. Dimotikalis and C. Skiadas, “Special issue – Communications in Statistics – Case studies and data analysis: 5th Stochastic Modeling Techniques and Data Analysis International Conference,” Commun. Stat.: Case Stud. Data Anal. Appl., vol. 6, no. 4, pp. 381-382, Oct. 2020, doi: 10.1080/23737484.2020.1850108.2022-06-02
63 P. Manolitzas, E. Grigoroudis, J. Christodoulou, and N. Matsatsinis, “S-MEDUTA: combining balanced scorecard with simulation and MCDA techniques for the evaluation of the strategic performance of an emergency department,” in GeNeDis 2018, Computational Biology and Bioinformatics, vol 1194, Advances in Experimental Medicine and Biology, P. Vlamos, Ed., Cham, Switzerland: Springer Nature, 2020, pp. 1–22, doi: 10.1007/978-3-030-32622-7_1.2022-06-01
64 V. Rusyn, and C. H. Skiadas, “Threshold method for control of chaotic oscillations,” in 12th Chaotic Modeling and Simulation International Conference, Springer Proceedings in Complexity, C. H. Skiadas, Y. Dimotikalis, Eds., Cham, Switzerland: Springer Nature, 2020, pp. 217–229, doi: 10.1007/978-3-030-39515-5_18.2022-05-31
65 V. Rusyn, A. Samila, and C. Skiadas, "Computer modeling and practical realization of chaotic circuit with a light-emitting diode," in Proceedings of SPIE - 14th International Conference on Correlation Optics 2019, vol 11369, O. V. Angelsky, Ed., Bellingham, WA: SPIE, 2020, doi: 10.1117/12.2550813.2022-05-27
66 E. Papachristou, and N. Bilalis, “Data analytics and application challenges in the childrenswear market - a case study in Greece,” in Product Lifecycle Management Enabling Smart X, vol 594, IFIP Advances in Information and Communication Technology, F. Nyffenegger, J. Ríos, L. Rivest, A. Bouras, Eds., Cham, Switzerland: Springer Nature, 2020, pp. 647–658, doi: 10.1007/978-3-030-62807-9_51.2022-05-27
67 E. Rapanaki, I.-D. Psychas, M., Marinaki, and Y. Marinakis, “An Artificial Bee Colony algorithm for the multiobjective energy reduction multi-depot vehicle routing problem,” in Learning and Intelligent Optimization, vol 11968, Lecture Notes in Computer Science, N. Matsatsinis, Y. Marinakis, P. Pardalos, Eds., Cham, Switzerland: Springer Nature, 2020, pp. 208–223, doi: 10.1007/978-3-030-38629-0_17.2022-05-19
68 D. Trachanatzi, M. Rigakis, A. Taxidou, M. Marinaki, Y. Marinakis, and N. Matsatsinis, “A novel solution encoding in the Differential Evolution algorithm for optimizing tourist trip design problems,” in Learning and Intelligent Optimization, vol 11968, Lecture Notes in Computer Science, N. Matsatsinis, Y. Marinakis, P. Pardalos, Eds., Cham, Switzerland: Springer Nature, 2020, pp. 253–267, doi: 10.1007/978-3-030-38629-0_21.2022-05-19
69 K. Zervoudakis, S. Tsafarakis, and P.-P, Sovatzidi, “A new hybrid Firefly – Genetic algorithm for the optimal product line design problem,” in Learning and Intelligent Optimization, vol 11968, Lecture Notes in Computer Science, N. Matsatsinis, Y. Marinakis, P. Pardalos, Eds., Cham, Switzerland: Springer Nature, 2020, pp. 284–297, doi: 10.1007/978-3-030-38629-0_23.2022-05-17
70 E. Tsakirakis, M. Marinaki, and Y. Marinakis, “A hybrid variation Harmony Search algorithm for the Team Orienteering Problem with capacity limitations,” in Learning and Intelligent Optimization, vol 11968, Lecture Notes in Computer Science, N. Matsatsinis, Y. Marinakis, P. Pardalos, Eds., Cham, Switzerland: Springer Nature, 2020, pp. 146–156, doi: 10.1007/978-3-030-38629-0_12.2022-05-17
71 E. Rapanaki, I.-D. Psychas, M. Marinaki, N. Matsatsinis, and Y. Marinakis, “A Krill Herd algorithm for the multiobjective energy reduction multi-depot vehicle routing problem,” in Machine Learning, Optimization, and Data Science, vol 12565, Lecture Notes in Computer Science, Cham, Switzerland: Springer Nature, 2020, pp. 434–447, doi: 10.1007/978-3-030-64583-0_39.2022-05-10
72 N. I. Spanoudakis, “Statecharts and agent technology: the past and future,” in Multi-Agent Systems and Agreement Technologies, vol 12520, Lecture Notes in Computer Science, N. Bassiliades, G. Chalkiadakis, D. de Jonge, Eds., Cham, Switzerland: Springer Nature, 2020, pp. 511–528, doi: 10.1007/978-3-030-66412-1_33.2022-05-10
73 N. Spanoudakis, K. Kostis, and K. Mania, "Argumentation for all," in Proceedings of the 35th ACM/SIGAPP Symposium on Applied Computing (SAC ’20), Brno, Czech Republic, 2020, pp. 980–982, doi: 10.1145/3341105.3374122.2022-05-05
74 S. Zhang, M. Diamantis, Y. Wang, J. Guo, I. Papamichail, M. Papageorgiou, L. Zhang, and J. S. Hu, “Joint queue estimation and max pressure control for signalized urban networks with connected vehicles,” in 2020 Forum Integr. Sustain. Transp. Syst. (FISTS), Delft, The Netherlands, 2020, pp. 211- 217, doi: 10.1109/FISTS46898.2020.9264889.2022-04-29
75 G. J. Tsinarakis, P. S. Spanoudakis, G. Arabatzis, N. C. Tsourveloudis, and L. Doitsidis, "Implementation of a petri-net based digital twin for the development procedure of an electric vehicle," in Mediterr. Conf. Control Autom. MED, 2020, pp. 862-867, doi: 10.1109/MED48518.2020.9182784.2022-01-25
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