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Improving Communication on Disastrous Events using Visual Simulation and Optimization Model
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Improving Communication on Disastrous Events using Visual Simulation and Optimization Model






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Improving Communication on Disastrous Events using Visual Simulation and Optimization Model Improving Communication on Disastrous Events using Visual Simulation and Optimization Model Presentation Transcript

  • Improving Communication on Disastrous Events using Visual Simulation and Optimization Model Erkki Kurkinen University of Jyväskylä International Disaster and Risk Conference IDRC Davos 2010, 30 May to 3 June 2010
  • Introduction • Communication between different emergency services units is vital in disastrous events • Lack of communcation may play an important role as a cause of failure in rescue operations • Lack of communication may be caused by the lack a common communication instructions between rescue organizations • Reports of some large accidents tend to show that lack of communication is a threath even for a high level decison making (Onnettomuustutkintakeskus 2004, 9/11 Commision report) • A decent communication directive for the communication is needed • To build a view of the communication, it can be simulated with a visual model • This simulation can be used for optimization and further to develop the communication directive
  • Targets of this study This study has three main targets: 1. Creating visual simulation model based on real data from emergency rescue operations 2. Optimizing the communication between parties using the optimization model to be developed 3. Creating communication directive for the optimized traffic Simulation Communication Optimization model directive emergency emergency emergency emergency
  • General simulation model • Simulation (Ruohonen, 2007) is • a numerical method utilising mathematical models • a procedure built in a form of mathematical functions and relations Decision variables Target Initial data Simulation variables • Simulation can be classified to be continuous, stochastic, deterministic or discrete event simulation (Ruohonen, 2007) • In this study a discrete event simulation model will be developed because the communication events are discrete and random
  • General discrete simulation model • General discrete simulation model is often called ”transaction-flow world view” (Scrieber et al. 2004 p.142) • In this type of the model transactions (=the simulated events) flow freely from one point to another competing of the heavily loaded serving resources • In this study those transactions are communication elements, such as voice, data blocks, location data elements, images and videos • The state of the model is changed randomly only at discrete time points • Transactions are served serially even if serving seems to happen simultaneously
  • Definitions • Discrete event simulation (Scrieber et al, 2004) – events are discrete – events are random – Events may partly be dependent of each other • Optimization (Nocedal et al, 1999) – Optimization is an iterative process done by running the simulation model in a computer starting with the initial values of variables until target variables are achieved • Communication – Any information exhange between the resecue organisations – covers variety of communication elements: voice,data, multimedia, Internet, television,radio
  • Model to be developed initial data simulation optimization create directive = attempts to - turned into  efficiency = to get the communicate a mathematical = # of attempts best method form and shown visually voice data Communication multimedia Simulation Optimization directive Internet Television radio
  • Optimization • Objective of this optimization is the efficiency in all communication • The efficiency in this study will approximated by the number of the attempts to get a free channel to communicate through the selected channel • The number of attempts is optimized with the model to be developed
  • Communication directive • Rescue authorites use a directive to communicate with each other to minimize the load on the communication channel, such as radio network • However, this type of directive does not automatically guarantee the most efficient communication in practice because it may limit communication possibilites • To give the optimized communication for the users also the directive must be optimized • In this study the optimized directive is the way for the most efficient method to communciate between parties
  • Conclusion • Communication is critical between different levels of all rescue organizations • Lack of communication and lack of the directives may cause severe problems in the perfomance of those organizations • By modelling the communication, based on real data, communication blockages can be found and will increase the efficiency of the systems • Based on the simulation and optimization results, decent communication directive will be presented
  • REFERENCES 1. Onnettomuustutkintakeskus, (2004) Tutkintaselostus A 1/2004 Y, Finland (full version available only in Finnish) 2. National Commission on Terrorist Attacks upon United States (200?), The 9/11 Commission report, Final report of the National Commission on Terrorist Attacks upon United States, Executive summary, USA 3. Farnham, Shelly, Pedersen Elin R., Kirkpatrick, Robert, (2006) Observation of Katrina/Rita Groove Deployment: Addressing Social and Communication Challenges of Ephemeral Groups, Proceedings of the 3rd International ISCRAM Conference (B. Van de Walle and M. Turoff, eds.), Newark, NJ (USA), May 2006 4. Ruohonen Toni (2007) Improving the Operation of an Emergency Department by Using a Simulation Model, Jyväskylä Studies in Computing, University of Jyväskylä, 2007 5. Schriber, Thomas J., Brunner, Daniel T., (2004) Inside discrete-event simulation software: how it works and why it matters, Proceedings of the 2004 Winter Simulation Conference R .G. Ingalls, M. D. Rossetti, J. S. Smith, and B. A. Peters, eds. 6. Nocedal Jorge, Wright, Stephen J. Numerical Optimization, Springer Science+Business Media, USA