Abstract
The article deals with the issue of material distribution under the conditions of uncertainty in disturbed or damaged logistics infrastructure due to natural disaster or extensive industrial accident. Possibilities of material distribution using a medium-size freight truck were analysed under the condition of the limited functionality and availability of logistics infrastructure. Requirements for the load capacity, flying range and number of Unmanned Aerial Vehicles (UAVs) that could replace distribution of material by trucks within a damaged logistics infrastructure were identified based on the theoretical model through discrete simulation.
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References
BCI: The BCI. BCI Supply Chain Resilience Report 2018. The BCI, Caversham, The Business Continuity Institute, 1 September 2018. https://www.thebci.org/. Accessed 18 Nov 2018
Bernatik, A., Senovsky, P., Senovsky, M., Rehak, D.: Territorial risk analysis and mapping. In: 14th Symposium on Loss Prevention and Safety Promotion in the Process Industries, LP 2013, vols. I and II, AIDIC SERVIZI SRL, Florence, pp. 79–84 (2013). https://doi.org/10.3303/CET1331014
Dvorak, Z., Sventekova, E., Rehak, D., Cekerevac, Z.: Assessment of critical infrastructure elements in transport. In: TRANSBALTICA 2017: Transportation Science and Technology, pp. 548–555. Elsevier Science, Vilnius (2017). https://doi.org/10.1016/j.proeng.2017.04.413
ESRI: World street map, 2 October 2018
EU Military Committee: EU Concept for Reception, Staging, Onward Movement and Integration (RSOI) for EU-led Military Operations. EU Military Commettee, Brussels (2012)
European Environment Agency: Economic losses from climate-related extremes (European Union), 27 February 2018. European Environment Agency. https://goo.gl/uxzsj7. Accessed 19 Nov 2018
Foltin, P., Gontarczyk, M., Swiderski, A., Zelkowski, J.: Evaluation model of the companies operating within logistic network. Arch. Transp. 36(4), 21–33 (2015). https://doi.org/10.5604/08669546.1185196
Foltin, P., Vlkovský, M., Mazal, J., Husák, J., Brunclík, M.: Discrete event simulation in future military logistics applications and aspects. In: Mazal, J. (ed.) MESAS 2017. LNCS, vol. 10756, pp. 410–421. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-76072-8_30
Forzieri, G., Cescatti, A., Batiste de Silva, F., Feyen, L.: Increasing risk over time of weather-related hazards to the European population: a data-driven prognostic study. LANCET Planet. Health 2017(5), e200–e208 (2017). https://doi.org/10.1016/S2542-5196(17)30082-7
Grohman, J.: Cormorant: Robotický létající náklaďák pro vojáky i civilisty. Hybrid.cz, 21 Nov 2016. https://www.hybrid.cz/cormorant-roboticky-letajici-nakladak-pro-vojaky-i-civilisty. Accessed 27 Nov 2018
Guha-Sapir, D., Hoyois, P., Wallemacq, P., Below, R.: Annual Disaster Statistical Review 2016: The Numbers and Trends. The International Disaster Database (2017). https://www.emdat.be/sites/default/files/adsr_2016.pdf. Accessed 10 Sep 2018
Hodicky, J., Prochazka, D.: Modelling and simulation paradigms to support autonomous system operationalization. In: Mazal, J., Fagiolini, A., Vasik, P. (eds.) MESAS 2019. LNCS, vol. 11995, pp. 361–371. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-43890-6_29
Hodicky, J., Özkan, G., Özdemir, H., Stodola, P., Drozd, J., Buck, W.: Dynamic modeling for resilience measurement: NATO resilience decision support model. Appl. Sci. 10(8), 1–10 (2020). https://doi.org/10.3390/app10082639
Kovács, G., Spens, K.: Humanitarian logistics in disaster relief operations. Int. J. Phys. Distrib. Logist. Manage. 37(2), 99–114 (2007). https://doi.org/10.1108/09600030710734820
Rehak, D., Novotny, P.: Bases for modelling the impacts of the critical infrastructure failure. Chem. Eng. Trans. 2016(1) (2016). https://doi.org/10.3303/CET1653016
Robinson, S.: Simulation: The Practice of Model Development and Use. Wiley, Chichester (2004)
Sedlacik, M., Odehnal, J., Foltin, P.: Classification of terrorism risk by multidimensional statistical methods. In: International Conference on Numerical Analysis and Applied Mathematics (ICNAAM). American Institute of Physics Inc. (2014). https://doi.org/10.1063/1.4912948
Sherman, N.: A Stochastic Model for Joint Reception, Staging, Onward Movement, and Integration (JRSOI). Air Force Institute of Technology, Wright-Patterson Air Force Base (2003)
Sturrock, W.K.-J.-D.: Simio and Simulation: Modeling, Analysis, Applications: Economy. CreateSpace Independent Publishing Platform, Scotts Valley (2013)
Topcu, O., Durak, U., Oguztuzun, H., Yilmaz, L.: Distributed Simulation. Springer, New York (2016). https://doi.org/10.1007/978-3-319-03050-0
Urban, R., Oulehlová, A., Malachová, H.: Computer simulation - efficient tool of crisis management. In: International Conference Knowledge-Based Organization, pp. 135–141. “Nicolae Balcescu” Land Forces Academy, Sibiu (2017)
Vlkovsky, M., Koziol, P., Grzesica, D.: Wavelet based analysis of truck vibrations during off-road transportation. In: The 14th International Conference on Vibration Engineering and Technology of Machinery (VETOMAC XIV), MATEC Web of Conferences, Lisbon (2018).
Zhang, F.: Electronic consultations to usability of TT Aviation Technology Co., Ltd products, 18 September 2019. (P. Foltin, Interviewer)
Acknowledgement
The paper has been written with the support of the project of long-term strategy of organization development: ROZVOLOG: Development of Capabilities and Sustainability of Logistics Support (DZRO ROZVOLOG 2016–2020) funded by the Ministry of Defence of the Czech Republic.
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Tulach, P., Foltin, P., Gesvret, M., Zlatník, D. (2021). Replacement Possibilities of the Medium-Size Truck Transport Capability by UAVs in the Disturbed Logistics Infrastructure. In: Mazal, J., Fagiolini, A., Vasik, P., Turi, M. (eds) Modelling and Simulation for Autonomous Systems. MESAS 2020. Lecture Notes in Computer Science(), vol 12619. Springer, Cham. https://doi.org/10.1007/978-3-030-70740-8_9
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