George Leventakis, Athanasios Sfetsos, Vasileios Gkrizis, Nikolas Athanasiadis, Stefan Tönjes, Spyros Kopsidas, et al. (2011). A Security Risk Analysis Framework for interconnected transportation systems. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The present paper introduces a comprehensive Transportation Security Risk Assessment Framework for assessing related risks and provides cohered contingency management procedures in interconnected, interdependent and heterogeneous transport networks. The proposed approach includes elements, methodological tools and approaches found in the literature, in addition to operational experience from the organization of major events.
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Duncan T. Wilson, Glenn I. Hawe, Graham Coates, & Roger S. Crouch. (2013). Scheduling response operations under transport network disruptions. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 683–687). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Modeling the complex decision problems faced in the coordination of disaster response as a scheduling problem to be solved using an optimization algorithm has the potential to deliver efficient and effective support to decision makers. However, much of the utility of such a model lies in its ability to accurately predict the outcome of any proposed solution. The stochastic nature of the disaster response environment can make such prediction difficult. In this paper we examine the effect of unknown disruptions to the road transport network on the utility of a disaster response scheduling model. The effects of several levels of disruption are measured empirically and the potential of using real-time information to revise model parameters, and thereby improve predictive performance, is evaluated.
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Dimitris Zisiadis, Spyros Kopsidas, Vassilis Grizis, George Thanos, George Leventakis, & Leandros Tassiulas. (2012). STAR-TRANS Modeling Language (STML) modeling risk in the STAR-TRANS risk assessment framework for interconnected transportation systems. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: The present paper introduces a high level modeling language, capable of expressing the concepts and processes of the Strategic Risk Assessment and Contingency Planning in Interconnected Transportation Networks (STAR-TRANS) framework. STAR-TRANS is a comprehensive transportation security risk assessment framework for assessing related risks that provides cohered contingency management procedures for interconnected, interdependent and heterogeneous transport networks. STAR-TRANS modeling Language (STML) is a domain specific language combining language simplicity with a very clear syntax, providing all the necessary elements (assets, threats, incidents, consequences etc.) to model the STAR-TRANS risk assessment framework. © 2012 ISCRAM.
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