Abstract
Many emergency situations involve injured people who need medical help and evacuation to a safe area. Usually there is not enough time to provide medical help to all the victims. So medical doctors have to make choices to help as much victims as possible, taking care of the distribution of victims in the crisis area and the priority of the victims related to the severity of the injuries. This paper describes an ant colony optimization algorithm to route medical doctors along the victims in a crisis area. We tested the algorithm in a simulated crisis environment. Two different routing strategies were implemented and compared with our algorithm.
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References
van Veelen, J., Storms, P., van Aart, C.: Effective and Efficient Coordination Strategies for Agile Crisis Response Organizations. In: International Workshop on Information Systems for Crisis Response and Management ISCRAM 2006 (2006)
Garner, A., Lee, A., Harrison, K., Schultz, C.H.: Comparative analysis of multiple-casualty incident triage algorithms. Annals of Emergency Medicine 38(5), 541–548 (2001)
Benson, D., Keonig, K., Schultz, C.: Disaster triage: START then SAVE - a new method of dynamic triage for victims of a catastrophic earthquake. Prehosp. Disaster Med. 11, 117–124 (1996)
Montemanni, R., Gambardella, L., Rizzoli, A., Donati, A.: A new algorithm for a Dynamic Vehicle Routing Problem based on Ant Colony System. In: Proceedings of Third International Workshop ANTS 2002, pp. 111–122 (2002)
Dorigo, M., Maniezzo, V., Colorni, A.: Ant System: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics Part B: Cybernetics 26(1), 29–41 (1996)
Dorigo, M., Gambardella, L.: Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. IEEE Transactions on Evolutionary Computation 1(1), 53–66 (1997)
Ellabib, I., Basir, O.A., Calamai, P.: An Experimental Study of a Simple Ant Colony System for the Vehicle Routing Problem with Time Windows. In: Proceedings of Third International Workshop ANTS 2002, pp. 53–64 (2002)
Guntsch, M., Middendorf, M., Schmeck, H.: An Ant Colony Optimization Approach to Dynamic TSP. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001), pp. 860–867 (2001)
Guntsch, M., Middendorf, M.: Applying Population Based ACO to Dynamic Optimization Problems. In: Proceedings of Third International Workshop ANTS 2002, pp. 111–122 (2002)
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© 2006 Springer-Verlag Berlin Heidelberg
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Tatomir, B., Rothkrantz, L. (2006). Ant Based Mechanism for Crisis Response Coordination. In: Dorigo, M., Gambardella, L.M., Birattari, M., Martinoli, A., Poli, R., Stützle, T. (eds) Ant Colony Optimization and Swarm Intelligence. ANTS 2006. Lecture Notes in Computer Science, vol 4150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11839088_36
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DOI: https://doi.org/10.1007/11839088_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38482-3
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