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Title
The game theory decision models for transport systems selection based on the SWOT analysis on the example of heavy and oversized goods transport

ISSN printed: 1733-8670, ISSN on-line: 2392-0378
Strzelczyk, Adriana1; Guze, Sambor2
URI: https://repository.am.szczecin.pl/handle/123456789/2849
2025-03-31
This article addresses the optimal choice of transport mode for a specific transport task. Knowing each branch’s limitations, strengths, and weaknesses facilitates decision-making when identifying them for use in a given situation. This is of particular importance when transporting oversized loads and heavy pieces. Therefore, this article aims to propose a new model of the game with nature based on SWOT analyses for transport systems selection for oversized and heavy loads. Firstly, for this solution, it is necessary to define measures for each of the four elements of a SWOT analysis (i.e., strengths, weaknesses, opportunities, and threats). Secondly, these four elements are the states of nature in a defined game with nature. Here, the transport mode builds the scenarios that are possible to select. The SWOT analysis determines the strategic position, market attractiveness (MA), and market position (MP) of transport modes. Next, applying very well-known decision-making criteria in the theory of games with nature makes it possible to create appropriate decision-making models for transport mode selection. The application of the method is shown in the example of selecting the most competitive modes of transport for oversized loads.
  1. Ahmad, F. & Al-Fagih, L. (2023) Game theory applications in micro and macroscopic simulation in transportation network: a comprehensive review. IEEE Access 11, pp. 93635‒93663, doi: 10.1109/ACCESS.2023.3308048.,
  2. Baum, R. & Wielkicki, W. (2024) Metoda SWOT jako narzędzie analizy strategicznej przedsiębiorstw agrobiznesu. Poznań: Wydawnictwo Akademii Rolniczej im. Augusta Ciesszkowskiego.,
  3. Bukvić, L., Pašagić Škrinjar, J., Abramović, B. &Zitrický, V. (2021) Route selection decision-making in an intermodal transport network using game theory. Sustainability 13 (8), 4443, doi: 10.3390/su13084443.,
  4. Chłopińska, E. & Gucma, M. (2020) Multicriteria optimization method of LNG distribution. TransNav: International Journal on Marine Navigation and Safety of Sea Transportation 14 (2), pp. 493‒497, doi: 10.12716/1001.14.02.30.,
  5. Chou, J.S. (2009) Generalized linear model-based expert system for estimating the cost of transportation projects. Expert Systems with Applications 36 (3), 1, pp. 4253‒4267, doi: 10.1016/j.eswa.2008.03.017.,
  6. Costello, D., Mooney, P. & Winstanley, A.C. (2001) Multi-objective optimisation on transportation networks. In: 4th AGILE Conference on Geographic Information Science, April 19‒21, Brno, Czech Republic, pp. 523‒530.,
  7. Gierszewska, G. & Romanowska, M. (2003) Analiza strategiczna przedsiębiorstwa. Warszawa: Polskie Wydawnictwo Ekonomiczne,
  8. Goodwin, P. & Wright, G. (2014) Decision Analysis for Management Judgment. John Wiley & Sons Inc.,
  9. Heath, A., Kunst, N. & Jackson, C. (Eds) (2024) Value of Information for Healthcare Decision-Making (1st ed.). Chapman and Hall/CRC, doi: 10.1201/9781003156109.,
  10. Howard, R.A. & Abbas, A.E. (2015) Foundations of Decision Analysis. Global Edition, Pearson,
  11. Hurwicz, L. (1951) Optimality criteria for decision making under ignorance. Statistics 1951, 370.,
  12. Islam, M.R., Mahmud, M.R. & Pritom, R.M. (2020) Transportation scheduling optimization by a collaborative strategy in supply chain management with TPL using chemical reaction optimization. Neural Computing and Applications 32, pp. 3649‒3674, doi: 10.1007/s00521-019-04218-5.,
  13. Jackson, C., Jalal, H., Heath, A., Kunst, N., Thom, H., Welton, N.J., Tuffaha, H. & Wilson, E. (2024) The expected value of perfect or partial perfect information. In: A. Heath, N. Kunst & C. Jackson (Eds) Value of Information for Healthcare Decision-Making, Chapman and Hall/CRC.,
  14. Khan, M.A. (2014) Transportation cost optimization using linear programming. In International Conference on Mechanical, Industrial and Energy Engineering (pp. 1‒5), 26‒27 December, Khulna, Bangladesh.,
  15. Kumar, P. (2015) Industrial Engineering and Management. Pearson, India.,
  16. Lasić, T., Rožić, T. & Stanković, R. (2023) Optimization of transport network using mathematical methods. Transportation Research Procedia 73, pp. 5‒16, doi: 10.1016/j. trpro.2023.11.885.,
  17. Loustau, P., Morency, C., Trépanier, M. & Gourvil, L. (2010) Travel time reliability on a highway network: estimations using floating car data. Transportation Letters 2 (1), pp. 27‒37, doi: 10.3328/TL.2010.02.01.27-37.,
  18. McNamee, P. & Celona, J. (2008) Decision Analysis for the Professional. SmartOrg, Inc.,
  19. Meng, X., Wang, Y., Jia, L. & Li, L. (2020) Reliability optimization of a railway network. Sustainability 12 (23), 9805, doi: 10.3390/su12239805.,
  20. Neumann, T. (2021) Comparative analysis of long-distance transportation with the example of sea and rail transport. Energies 14 (6), 1689, doi: 10.3390/en14061689.,
  21. Papadimitriou, C.H. (1985) Games against nature. Journal of Computer and System Sciences 31 (2), pp. 288‒301, doi: 10.1016/0022-0000(85)90045-5.,
  22. Pažek, K. & Rozman, Č. (2009) Decision making under conditions of uncertainty in agriculture: a case study of oil crops. Poljoprivreda 15 (1), pp. 45‒50.,
  23. Pierścionek, Z. (2006) Strategie konkurencji i rozwoju przedsiębiorstwa. Warszawa: Wydawnictwo Naukowe PWN.,
  24. Raicu, S., Popa, M. & Costescu, D. (2022) Uncertainties influencing transportation system performances. Sustainability 14 (13), 7660, doi: 10.3390/su14137660.,
  25. Raiffa, H. (1968) Decision Analysis: Introductory Lectures on Choices Under Uncertainty. Addison-Wesley.,
  26. Savage, L.J. (1951) The theory of statistical decision. Journal of the American Statistical Association 46 (253), pp. 55‒67.,
  27. Simon, H.A. (1959) Theories of decision-making in economics and behavioral science. The American Economic Review 49 (3), pp. 253‒283.,
  28. Tulsian, P.C. & Pandey, V. (2016) Quantitative Techniques: Theory and Problems. Pearson India.,
  29. Villalobos, I.A., Poznyak, A.S. & Tamayo, A.M. (2008) Urban traffic control problem: a game theory approach. IFAC Proceedings Volumes 41 (2), pp. 7154‒7159, doi: 10.3182/20080706-5-KR-1001.01213.,
  30. Wald, A. (1949) Statistical decision functions. The Annals of Mathematical Statistics, pp. 165‒205.,

Title

The game theory decision models for transport systems selection based on the SWOT analysis on the example of heavy and oversized goods transport

Pages

Figures

3

Tables

7

ISSN printed

1733-8670

ISSN on-line

2392-0378

DOI

10.17402/628

Type

Original scientific article

Journal

81 Scientific Journals of the Maritime University of Szczecin, no. 81 / 2025

Publisher

Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Akademia Morska w Szczecinie

Copyright Holder

Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Akademia Morska w Szczecinie

Published

2025-03-31

Recieved

2024-12-08

Accepted

2025-01-13

Funding

No data

Keywords

games with nature, heavy goods, oversized goods, multicriteria optimization, SWOT, EOL, EVPI, transport nodes selection

URI:

https://repository.am.szczecin.pl/handle/123456789/2849

Language

English

Authors

Strzelczyk, Adriana1; Guze, Sambor2

Affiliation

1 Maritime School Complex in Gdańsk 8 Wyzwolenia St., 80-537 Gdańsk, Poland, liada@interia.pl
2 2 Gdynia Maritime University 81-87 Morska St., 81-225 Gdynia, Poland, sambor@am.gdynia.pl

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