FACTOR ANALYSIS METHOD APPLICATION FOR CONSTRUCTING OBJECTIVE FUNCTIONS OF OPTIMIZATION IN MULTIMODAL TRANSPORT PROBLEMS
Article Sidebar
Open full text
Issue Vol. 11 No. 4 (2021)
-
SINGULAR INTEGRATION IN BOUNDARY ELEMENT METHOD FOR HELMHOLTZ EQUATION FORMULATED IN FREQUENCY DOMAIN
Tomasz Rymarczyk, Jan Sikora4-8
-
APPLICATION OF THE THREAT INTELLIGENCE PLATFORM TO INCREASE THE SECURITY OF GOVERNMENT INFORMATION RESOURCES
Bohdan Nikolaienko, Serhii Vasylenko9-13
-
INDIRECT INFORMATION HIDING TECHNOLOGY ON A MULTIADIC BASIS
Volodymyr Barannik, Natalia Barannik, Oleksandr Slobodyanyuk14-17
-
SELECTED APPLICATIONS OF DEEP NEURAL NETWORKS IN SKIN LESION DIAGNOSTIC
Magdalena Michalska18-21
-
EFFICIENT LINE DETECTION METHOD BASED ON 2D CONVOLUTION FILTER
Paweł Kowalski, Piotr Tojza22-27
-
FACTOR ANALYSIS METHOD APPLICATION FOR CONSTRUCTING OBJECTIVE FUNCTIONS OF OPTIMIZATION IN MULTIMODAL TRANSPORT PROBLEMS
Serhii Zabolotnii, Artem Honcharov, Sergii Mogilei28-31
-
QUALITY OF SATELLITE COMMUNICATION IN SELECTED MOBILE ANDROID SMARTPHONES
Przemysław Falkowski-Gilski32-37
-
CHROMATIC DISPERSION COMPENSATION IN EXISTING FIBER OPTIC TELECOMMUNICATION LINES WITH THE GROWING BIT RATES NEEDS OF DWDM SYSTEM
Tomasz Bobruk38-41
-
FIBRE OPTIC BRAGG STRUCTURES WITH MONOTONIC APODISATION CHARACTERISTICS
Jacek Klimek42-46
-
ON THE CAPACITY OF SOLAR CELLS UNDER PARTIAL SHADING CONDITIONS
Mateusz Bartczak47-50
-
CONTROLLING A FOUR-WIRE THREE-LEVEL AC/DC CONVERTER WITH INDEPENDENT POWER CONTROL IN EVERY PHASE
Bartłomiej Stefańczak51-54
-
METHOD OF MEASUREMENT AND REDUCTION OF THE ELECTROMAGNETIC DISTURBANCES INDUCTED BY SWITCHING SURGES IN LV CIRCUITS
Patryk Wąsik55-61
-
INCREASING THE COST-EFFECTIVENESS OF IN VITRO RESEARCH THROUGH THE USE OF TITANIUM IN THE DEVICE FOR MEASURING THE ELECTRICAL PARAMETERS OF CELLS
Dawid Zarzeczny62-66
-
ELLIPSOMETRY BASED SPECTROSCOPIC COMPLEX FOR RAPID ASSESSMENT OF THE Bi2Te3-xSex THIN FILMS COMPOSITION
Vladimir Kovalev, Saygid Uvaysov, Marcin Bogucki67-74
-
APPLICATION OF LOW-COST PARTICULATE MATTER SENSORS FOR MEASUREMENT OF POLLUTANTS GENERATED DURING 3D PRINTING
Jarosław Tatarczak75-77
Archives
-
Vol. 13 No. 4
2023-12-20 24
-
Vol. 13 No. 3
2023-09-30 25
-
Vol. 13 No. 2
2023-06-30 14
-
Vol. 13 No. 1
2023-03-31 12
-
Vol. 12 No. 4
2022-12-30 16
-
Vol. 12 No. 3
2022-09-30 15
-
Vol. 12 No. 2
2022-06-30 16
-
Vol. 12 No. 1
2022-03-31 9
-
Vol. 11 No. 4
2021-12-20 15
-
Vol. 11 No. 3
2021-09-30 10
-
Vol. 11 No. 2
2021-06-30 11
-
Vol. 11 No. 1
2021-03-31 14
-
Vol. 10 No. 4
2020-12-20 16
-
Vol. 10 No. 3
2020-09-30 22
-
Vol. 10 No. 2
2020-06-30 16
-
Vol. 10 No. 1
2020-03-30 19
-
Vol. 9 No. 4
2019-12-16 20
-
Vol. 9 No. 3
2019-09-26 20
-
Vol. 9 No. 2
2019-06-21 16
-
Vol. 9 No. 1
2019-03-03 13
Main Article Content
DOI
Authors
Abstract
The paper regards a specific class of optimization criteria that possess features of probability. Therefore, constructing objective function of optimization problem, the importance is attached to probability indices that show the probability of some criterial event or events to occur. Factor analysis has been taken for the main method of constructing objective function. Algorithm for constructing objective function of optimization is done for criterion of minimization risk level in multimodal transportations that demanded demonstration data. The application of factor analysis in classical problem solution was shown to give the problem a more distinct analytical interpretation in solving it.
Keywords:
References
Ayed H., Galvez-Fernandez C., Habbas Z., Khadraoui D.: Solving time-dependent multimodal transport problems using a transfer graph model. Computers and Industrial Engineering 61, 2011, 391–401 [http://doi.org/10.1016/j.cie.2010.05.018]. DOI: https://doi.org/10.1016/j.cie.2010.05.018
Ayed H., Habbas Z., Khadraoui D., Galvez-Fernandez C.: A parallel algorithm for solving time dependent multimodal transport problem. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC, 2011, 722–727 [http://doi.org/10.1109/ITSC.2011.6082973]. DOI: https://doi.org/10.1109/ITSC.2011.6082973
Boyd K. C.: Factor analysis. The Routledge Handbook of Research Methods in the Study of Religion 2013, 204–216 [http://doi.org/10.4324/9780203154281-22].
Chandrakantha L.: Using excel solver in optimization problems. John Jay College of Criminal Justice of CUNY, 2014, 42–49.
Elias D., Nadler B., Nadler F., Hauger G.: OPTIHUBS – Multimodal Hub Process Optimization by Means of Micro Simulation. Transportation Research Procedia 14, 2016, 457–466 [http://doi.org/10.1016/j.trpro.2016.05.098]. DOI: https://doi.org/10.1016/j.trpro.2016.05.098
Ezeokwelume O.: Solving linear programming problems and transportation problems using excel solver. International Journal of Scientific & Engineering Research 7(9), 2016, 134–142.
Flórez J. E., Torralba A., García J., Linares López C., García-Olaya A., Borrajo D.: TIMIPLAN: An Application to Solve Multimodal Transportation Problems. Scheduling and Planning Applications Workshop 2010.
García J., Florez J. E., Torralba A., Borrajo D., López C. L., García-Olaya A., Sáenz J.: Combining linear programming and automated planning to solve intermodal transportation problems. European Journal of Operational Research 227, 2013, 216–226. DOI: https://doi.org/10.1016/j.ejor.2012.12.018
Honcharov A., Mogilei S.: Solving multimodal transportation problems by different program means. Bulletin of Cherkasy State Technological University 3, 2020, 67–74.
Jennrich R. I., Bentler P. M.: Exploratory Bi-Factor Analysis. Psychometrika 76(4), 2011, 537–549 [http://doi.org/10.1007/s11336-011-9218-4]. DOI: https://doi.org/10.1007/s11336-011-9218-4
Journal I., Factor I.: Computational and Mathematical Methods in Medicine. Bio Med Research International 1, 2015, 2–4. DOI: https://doi.org/10.1155/2015/685036
Klami A., Virtanen S., Leppaaho E., Kaski S.: Group Factor Analysis. IEEE Transactions on Neural Networks and Learning Systems 26(9), 2015, 2136–2147 [http://doi.org/10.1109/TNNLS.2014.2376974]. DOI: https://doi.org/10.1109/TNNLS.2014.2376974
Lin C. C., Lin S. W.: Two-stage approach to the intermodal terminal location problem. Computers and Operations Research 67, 2016, 113–119 [http://doi.org/10.1016/j.cor.2015.09.009]. DOI: https://doi.org/10.1016/j.cor.2015.09.009
Ovcharuk V., Vovkodav N., Kryvets T., Ovcharuk I.: Linear programming in Mathcad on the example of solving the transportation problem. Scientific Works of NUFT 21(4), 2015, 110–117.
Sengamalaselvi J.: Solving transportation problem by using Matlab. International Journal of Engineering Sciences & Research Technology 6(1), 2017, 374–381 [http://doi.org/10.5281/zenodo.259588].
Slavova-Nocheva M.: Competitiveness of the transport market in Bulgaria. Economic Studies 21(3), 2012, 15–24.
Vats B., Kumar Singh A.: Solving transportation problem using excel solver for an optimal solution. MIT International Journal of Mechanical Engineering 6(1), 2016, 18–20.
Verga J., Silva R. C., Yamakami A.: Multimodal transport network problem: Classical and innovative approaches. Studies in Fuzziness and Soft Computing, Springer Verlag 358, 2018, 299–332 [http://doi.org/doi:10.1007/978-3-319-62359-7_14]. DOI: https://doi.org/10.1007/978-3-319-62359-7_14
Virtanen S., Klami A., Khan S.A., Kaski S.: Bayesian group factor analysis. The Journal of Machine Learning Research 22, 2012, 1269–1277.
Zabolotnii S., Mogilei S., The methods for determining the parameters of the objective function of multimodal transportation risk. Proceedings of V International Scientific-Practical Conference “ITEST-2020”, 2020, 114–115.
Zabolotnii S., Mogilei S.: Optimization of the method of constructing reference plans of multimodal transport problem. Technological audit and production reserves 2(45), 2019, 15–20 [http://doi.org/10.15587/2312-8372.2019.154561]. DOI: https://doi.org/10.15587/2312-8372.2019.154561
Zelenika R., Sever D., Zebec S., Pirš B.: Logistic operator: Fundamental factor in rational production of services in multimodal transport. Promet - Traffic&Transportation 17(1), 2005, 43–53.
Zhao S., Gao C., Mukherjee S., Engelhardt B. E.: Bayesian group factor analysis with structured sparsity. Journal of Machine Learning Research 17, 2016, 1–47.
Article Details
Abstract views: 382
License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
