Discrete Transportation System’s Availability Problem in Case of Critical Situation Sets

Jacek Mazurkiewicz; Tomasz Walkowiak

doi:10.2478/ttj-2013-0023

Abstract

The paper discusses the discrete transportation system’s (DTS) availability problem in case of the critical situation, which happens during its ordinary work. The formal model of the transportation system suitable for modelling based on the system behaviour observation is proposed. Monte Carlo approach is in use for a simulation. The system’s availability is calculated as global metric to find if the system is able to realise the loaded set of tasks. The critical situation discussed there is caused by reliability, as well as by functional and human reasons. No restriction on the system’s topology and on a kind of distribution describing the system’s functional and reliability parameters is the main advantage of the approach. The proposed solution seems to be essential for the owner and administrator of the transportation systems.

References

1. Barcelo, J., Codina, E., Casas, J., Ferrer, J. L., Garcia, D. (2005). Microscopic Traffic Simulation: a Tool for the Design, Analysis and Evaluation of Intelligent Transportation Systems. Journal ofIntelligent and Robotic Systems: Theory and Applications, 41, 173-203.10.1007/s10846-005-3808-2
Search in Google Scholar
2. Barlow, R. and Proschan, F. (1996). Mathematical Theory of Reliability. Philadelphia: Society for Industrial and Applied Mathematics.10.1137/1.9781611971194
Search in Google Scholar
3. Ben-Akiva, M., Cuneo, D., Hasan, M., Jha, M., Yang, Q. (2003). Evaluation of Freeway Control Using a Microscopic Simulation Laboratory. Transportation Research, Part C (Emerging Technologies), 11C, 29-50.10.1016/S0968-090X(02)00020-7
Search in Google Scholar
4. Birta, L. & Arbez, G. (2007). Modelling and Simulation: Exploring Dynamic System Behaviour. London: Springer Verlag.
Search in Google Scholar
5. Burt, C. N. & Caccetta, L. (2007). Match Factor for Heterogeneous Truck and Loader Fleets. International Journal of Mining, Reclamation and Environment, 21, 262-270.10.1080/17480930701388606
Search in Google Scholar
6. Duinkerken, M.B., Dekker, R., Kurstjens, S.T.G.L., Ottjes, J.A. & Dellaert, N.P. (2006). Comparing Transportation Systems for Inter-Terminal Transportation at the Maasvlakte Container Terminals. OR Spectrum, 28, 469-493.10.1007/s00291-006-0056-1
Search in Google Scholar
7. Fishman, G. (1996). Monte Carlo: Concepts, Algorithms, and Applications. New-York, Berlin, Heidelberg: Springer-Verlag.10.1007/978-1-4757-2553-7
Search in Google Scholar
8. Gartner, N., Messer, C.J., Rathi, A.K. (1998). Traffic Flow Theory and Characteristics, T.R. Board, (Ed.) (125 p.). Texas, Austin: University of Texas at Austin.
Search in Google Scholar
9. Gold, N., Knight, C., Mohan, A., Munro, M. (2004). Understanding service-oriented software. IEEESoftware, 21, 71-77.10.1109/MS.2004.1270766
Search in Google Scholar
10. Ioannou, P.A. (2008). Intelligent Freight Transportation. Carolina: Taylor and Francis Group.10.1201/9780849307744
Search in Google Scholar
11. Krzyzanowska, J. (2007). The Impact of Mixed Fleet Hauling on Mining Operations at Venetia Mine. Journal of The South African Institute of Mining and Metallurgy, 107, 215-224.
Search in Google Scholar
12. Liu, H., Chu, L., Recker, W. (2004). Performance Evaluation of ITS Strategies Using Microscopic Simulation. In Proceedings of the 7th International IEEE Conference on Intelligent Transportation Systems, Oct., 3-6, 2004 (pp. 255-270). Washington D. C.: IEEE Computer Society.
Search in Google Scholar
13. Sanso, B., Milot, L. (1999). Performability of a Congested Urban-Transportation Network when Accident Information is Available. Transportation Science, 33(1), 10-21.10.1287/trsc.33.1.68
Search in Google Scholar
14. Taylor, M.A.P., Woolley, J.E., Zito, R. (2000). Integration of the Global Positioning System and Geographical Information Systems for Traffic Congestion Studies. Transportation Research Part C(Emerging Technologies), 8C, 257-285.10.1016/S0968-090X(00)00015-2
Search in Google Scholar
15. Vis, I.F. (2006). A. Survey of Research in the Design and Control of Automated Guided Vehicle Systems. European Journal of Operational Research, 170, 677-709.
Search in Google Scholar
16. Walkowiak, T., Mazurkiewicz, J. (2009). Analysis of Critical Situations in Discrete Transportation Systems. In Proceedings of International Conference on Dependability of Computer Systems, Brunow, Poland, June 30-July 2, 2009, (pp. 364-371). Los Alamitos: IEEE Computer Society Press.
Search in Google Scholar
17. Walkowiak, T., Mazurkiewicz, J. (2008). Availability of Discrete Transportation System Simulated by SSF Tool. In Proceedings of International Conference on Dependability of Computer Systems, Szklarska Poreba, Poland, June, 2008 (pp. 430-437). Los Alamitos: IEEE Computer Society Press.
Search in Google Scholar
18. Walkowiak, T. & Mazurkiewicz, J. Functional Availability Analysis of Discrete Transportation System Realized by SSF Simulator. In ‘Computational Science - ICCS 2008’, the 8th International Conference, Krakow, Poland, June 2008, part I (pp. 671-678). Springer-Verlag, LNCS 5101.10.1007/978-3-540-69384-0_72
Search in Google Scholar
19. Walkowiak, T., Mazurkiewicz, J. (2010). Algorithmic Approach to Vehicle Dispatching in Discrete Transportation Systems. In Jarosław Sugier et al. (Eds.), Technical approach to dependability (pp. 173-188). Wroclaw: Oficyna Wydawnicza Politechniki Wroclawskiej.
Search in Google Scholar
20. Walkowiak, T., Mazurkiewicz, J. (2010). Functional Availability Analysis of Discrete Transportation System Simulated by SSF Tool. International Journal of Critical Computer-Based Systems, 1(1-3), 255-266.10.1504/IJCCBS.2010.031718
Search in Google Scholar
21. Walkowiak, T., Mazurkiewicz, J. (2010). Soft Computing Approach to Discrete Transportation System Management. In L. Rutkowski et al. (Eds.), Lecture Notes in Computer Science. Lecture Notes inArtificial Intelligence, vol. 6114 (pp. 675-682). Berlin-Heidelberg: Springer-Verlag.
Search in Google Scholar

Discrete Transportation System’s Availability Problem in Case of Critical Situation Sets

Abstract

Paradigm

My account