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Real-Time Emergency Response Fleet Deployment: Concepts, Systems, Simulation & Case Studies

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Dynamic Fleet Management

Part of the book series: Operations Research/Computer Science Interfaces Series ((ORCS,volume 38))

Abstract

Dynamic response to emergencies requires real time information from transportation agencies, public safety agencies and hospitals as well as the many essential operational components. In emergency response operations, good vehicle dispatching strategies can result in more efficient service by reducing vehicles’ travel times and system preparation time and the coordination between these components directly influences the effectiveness of activities involved in emergency response. In this chapter, an integrated emergency response fleet deployment system is proposed which embeds an optimization approach to assist the dispatch center operators in assigning emergency vehicles to emergency calls, while having the capability to look ahead for future demands. The mathematical model deals with the real time vehicle dispatching problem while accounting for the service requirements and coverage concerns for future demand by relocating and diverting the on-route vehicles and remaining vehicles among stations. A rolling-horizon approach is adopted in the model to reduce the relocation sites in order to save computation time. A simulation program is developed to validate the model and to compare various dispatching strategies

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Reference

  • Ball, M. O and F.L. Lin, Reliability Model Applied to Emergency Service Vehicle Location, Operations Research 41, pp.18-36 (1993).

    Google Scholar 

  • Brotcorne L, G. Laporte and F. Semet, Ambulance Location and Relocation Models, Eur J Opl Res, Vol 147, pp. 451-463 (2003).

    Article  Google Scholar 

  • Brown, G.G. and R. McBride, Solving Generalized Networks, Management Science, Vol. 20, pp. 1497-1523 (1985).

    Google Scholar 

  • Carter, G. and E. Ignall, A Simulation Model of Fire Department Operations, IEEE System Science and Cybernetics, Vol. 5, pp. 282-293 (1970).

    Google Scholar 

  • Catrysse, D. and Van Wassenhove, L.N, A Survey of Algorithms for the Generalized Assignment Problem,European Journal of Operational Research, Vol. 60, pp. 260-272 (1993).

    Article  Google Scholar 

  • Chabini, I., Discrete Dynamic Shortest Path Problems in Transportation Application, Transportation Research Record, No. 1645,pp. 170-175 (1998).

    Article  Google Scholar 

  • Chaiken, J. and R. Larson, Methods for Allocating Urban Emergency Units: A Survey, Management Science, 19, pp. 110-130 (1998).

    Google Scholar 

  • Chang, E., Traffic Estimation for Proactive Freeway Traffic Control, Transportation Research Record, No.1679, pp. 81-86 (1999).

    Article  Google Scholar 

  • Chang, M. F. and D. C. Gazis, Traffic Density Estimation with Consideration of Lane Changing, Transportation Science, Vol. 9, No. 4, pp. 308-320 (1975).

    Article  Google Scholar 

  • Chu, P.C. and J.E. Beasley, A Genetic Algorithms for the Generalized Assignment Problem, Camp. Operations Research 24 (1), pp.17-23 (1997).

    Article  Google Scholar 

  • Church, R. L. and C. Revelle, The Maximal Covering Location Problem, Papers of the Regional Science Association, Vol. 32 , pp. 101-118 (1974).

    Article  Google Scholar 

  • Cooke, K. and E. Halsey, The Shortest Route Through a Network with Time-Dependent Internodal Transit Times, Journal of Mathematical Analysis and Applications, Vol. 14, pp. 493-498 (1966).

    Article  Google Scholar 

  • Cragg, C. A., and M. J. Demetsky, Final Report: Simulation Analysis of Route Diversion Strategies for Freeway Iincident Management, VTRC 95-R11, Traffic Research Advisory Committee, FHWA, USDOT (1995).

    Google Scholar 

  • Daskin, M., A Maximum Expected Covering Location Model Formulation, Properties and Heuristic Solution. Transportation Science, Vol. 17, 48-70 (1983)

    Google Scholar 

  • Dijkstra, E. W., A Note on Two Problems in Connexion with Graphs, Numerische Mathematik, 1, pp. 269-271 (1959).

    Article  Google Scholar 

  • Eldor, M., Demand predictors for computerized freeway control systems”, Proceedings of the 7th International Symposium on Transportation and Traffic Theory, Kyoto, Japan, pp. 341-358 (1977).

    Google Scholar 

  • Fisher, M. L., An Applications Oriented Guide to Lagrangian Relaxation, Interface, Vol. 15, pp. 10-21 (1985).

    Google Scholar 

  • Fisher, M.L., R. Jaikumar and L.N. Wassenhove, A Multiplier Adjustment Method for the Generalized Assignment Problems”. Management Science 32, 1986, pp. 1095-1103 (1986).

    Google Scholar 

  • Fitzsimmons, J., A Methodology for Emergency Ambulance Deployment, Management Science, Vol. 19, No. 6, pp. 627-636 (1973).

    Google Scholar 

  • Gafarian, A.V., J. Paul, and T. L. Ward, Discrete Time Series Models of a Freeway Density Process, Proceedings of the 7th International Symposium on Transportation and Traffic Theory, Kyoto, Japan, pp.387-411 (1977).

    Google Scholar 

  • Gendreau, M, G. Laporte and F., Semet, A Dynamic Model and Parallel Tabu Search Heuristic for Real-Time Ambulance Relocation, Parallel Comput, 27, pp. 1641–1653 (2001).

    Article  Google Scholar 

  • Gendreau, M, G. Laporte, and F. Semet, The Maximal Expected Coverage Relocation Problem for Emergency Vehicles, Journal of Operation Research Society, Vol. 57, (1), pp. 22-28 (2005).

    Article  Google Scholar 

  • Goldberg, J., Dietrich, R., Chen, J., M. Mitwasi, Validating and Applying a Model for Locating Emergency Medical Vehicles in Tucson, AZ, European Journal of Operational Research, No.49, pp. 308-324 (1990).

    Article  Google Scholar 

  • Goldberg, J. and F. Szidarovszky, Method for Solving Nonlinear Equations Used in Evaluating Emergency Vehicle Busy Probabilities, Operations Research, Vol. 39, pp. 903-916 (1991a).

    Article  Google Scholar 

  • Goldberg, J., and L. Paz, Locating Emergency Vehicle Bases when Service Time Depends on Call Location, Transportation Science, Vol. 25, No.4, pp. 264-280 (1991b).

    Google Scholar 

  • Haghani, A., H. Hu, and Q. Tian, An Optimization Model for Real-Time Emergency Vehicle Dispatching and Routing, Proceeding CD of the 82 nd annual meeting of the Transportation Research Board, Washington, D.C., 2003.

    Google Scholar 

  • Hakimi, S., Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph, Operations Research 12, pp. 450-459 (1964).

    Google Scholar 

  • Hall, R., The Fastest Path through a Network with Random Time-Dependent Travel Times”, Transportation Science, Vol. 20, No. 3, pp. 182-188 (1986).

    Google Scholar 

  • Hoffman, C. and Janko, J., Travel Time as a Basis of the LISB Guidance Strategy, Proceedings of IEEE Road Traffic Control Conference, IEEE, New York, pp. 6-10 (1988).

    Google Scholar 

  • Hogan, K. and C. ReVelle, Concepts and Applications of Backup Coverage, Management Science, Vol. 32, pp. 1434-1444 (1986).

    Google Scholar 

  • Huisken, G., Soft-Computing Techniques Applied to Short-term Traffic Flow Forecasting, Systems Analysis Modeling Simulation, Vol.43-2, pp. 165-173 (2003).

    Article  Google Scholar 

  • Ignall, E.D., P. Kolesar, and W.E. Walker, Using Simulation To Develop and Validate Analytic Models: Some Case Studies, Operations Research, Vol. 26, No. 2, pp. 237-253 (1978).

    Google Scholar 

  • Kaysi, I., M. Ben-Akiva and H. Koutsopulos, An Integrated Approach to Vehicle Routing and Congestion Prediction for Real-Time Driver Guidance, Transportation Research Record, Vol. 1408, pp. 66-74 (1993).

    Google Scholar 

  • Kolesar, P., W. E. Walker, J. Hausner, Determining the Relation between Fire Engine Travel Times and Travel Distances in New York City Companies, Oper. Res., 23(4), pp. 614–627 (1975a).

    Google Scholar 

  • Larson, R., A Hypercube Queuing Model for Facility Location and Redistricting in Urban Emergency Services, Comput. & Ops. Res., Vol. 1, pp. 67-95 (1974).

    Article  Google Scholar 

  • Larson, R., Approximating the Performance of Urban Emergency Service Systems, Operations Research, Vol.23, No.5, pp. 845-868 (1975).

    Google Scholar 

  • Lorena, L.A.N. and M.G. Narciso, Relaxation Heuristics for a Generalized Assignment Problem, European Journal of Operational Research, Vol. 19, No. 3, pp. 600-610 (1996).

    Article  Google Scholar 

  • Lorena, L., M. G. Narciso, J. E. Beasley (2002); A Constructive Genetic Algorithm for the Generalized Assignment Problem, http://www.lac.inpe.br/∼ lorena/gap/CGA-PGA-2000.pdf

    Google Scholar 

  • Marinov, V. and C. Revelle, Siting Emergency Services, in Facility Location: A Survey of articles, applications and methods, edited by: Drezner, Z, Springer Series in Operations Research, pp. 199-222 (1995).

    Google Scholar 

  • Martello, S., W. R. Pulleyblank, P. Toth, and D. de Werra, Balanced Optimization Problems, Operations Research Letters 3, pp.275-278 (1984).

    Article  Google Scholar 

  • Nahi, N.E., Freeway Ttraffic Data Processing, Proceedings of the IEEE, 61, No. 5, pp. 537-541 (1973).

    Article  Google Scholar 

  • Narciso, M.G. and L.A.N. Lorena, “Lagrangian/surrogate relaxation for generalized assignment problems”, European Journal of Operational Research, Vol. 114, No. 1, pp. 165-177 (1999).

    Article  Google Scholar 

  • Nicholson H. and C. D. Swann, The Prediction of Traffic Flow Volumes Based on Spectral Analysis, Transportation Research Record, Vol. 8, pp. 533-538 (1974).

    Google Scholar 

  • Nulty, W. G. and M. A. Trick, GNO/PC Generalized Network Optimization System, O.R. Letters, Vol. 2, pp. 101-112 (1988).

    Article  Google Scholar 

  • ReVelle, C., and K. Hogan., A Reliability-Constrained Siting Model with Local Estimates of Busy Fractions, Environment and Planning B: Planning and Design, 15, pp. 143-152 (1988).

    Article  Google Scholar 

  • Revelle, C., Extension and Prediction in Emergency Service Siting Models, European Journal of Operational Research, Vol. 40, pp. 58-69 (1989).

    Article  Google Scholar 

  • Revelle, C. , “A Perspective on Location Science, Location Science, 5, No.1” pp. 3-13 (1997).

    Article  Google Scholar 

  • Ross, G. T. and M. S. Soland, A Branch and Bound Algorithm for the Generalized Assignment Problem, Mathematical Programming 8, pp. 91-103 (1975).

    Article  Google Scholar 

  • Savas, E.S., Simulation and Cost-Effectiveness Analysis of New York’s Emergency Ambulance Service. Management Science, Vol. 15, No. 12, pp. 608-627 (1969).

    Google Scholar 

  • Schilling, D. A., D. Elzinga, J. Cohon, R. Church and C. Revelle, The TEAM/FLEET Mmodels for Simultaneous Facility and Equipment Siting, Transportation Science, 13(2), pp. 163-175 (1979).

    Google Scholar 

  • Schilling, D. A., J. Vaidyanathan and R. Barkhi, A Review of Covering Problems in Facility Location, Location Science, Vol. 1, pp. 25-55 (1993).

    Google Scholar 

  • Shantikumar, J.G., and R.G. Sargent, A Unifying View of Hhybrid Simulation/Analytic Models and Modeling, Operations Research, Vol. 31, No. 6, pp. 1030-1052 (1983).

    Google Scholar 

  • Smith, B., Demetsky, M., Short-Term Traffic Flow Prediction: Neural Network Approach, Transportation Research Record, No. 1453, pp. 98-104 (1995).

    Google Scholar 

  • Stephanedes, Y. J., P.G. Michalopoulos, and R.A. Plum, Improved Estimation of Traffice Flow for Real-Time Control, Transportation Research Record, Vol. 795, pp. 28-39 (1981).

    Google Scholar 

  • Toregas, C., Swain, R., ReVelle, and C. Bergman, L., The Location of Emergency Service Facilities, Operations Research, Vol. 19-6, pp. 1363-1373 (1971).

    Google Scholar 

  • Toregas, C., Swain, R., ReVelle, C. and Bergman, L., Reply to Rao’s Note on the Location of Emergency Service Facilities, Operations Research, Vol. 22-6, pp. 1262-1267 (1974).

    Google Scholar 

  • Trick, M. A., A Linear Relaxation Heuristic for the Generalized Assignment Problem, Naval Research Logistics, Vol. 39, pp. 137-152 (1992).

    Article  Google Scholar 

  • Yang, Saini, Masoud Hamedi and Ali Haghani, An On-line Emergency Vehicle Dispatching and Routing Model with Area Coverage Constraints, Transportation Research Record, No. 1923, pp. 1-9 (2006).

    Google Scholar 

  • Ziliaskopoulos, A., and H. Mahmassani, Time Dependent, Shortest-Path Algorithm for Real-Time Intelligent Vehicle Highway System Applications, Transportation Research Record 1408, pp. 94-100 (1993).

    Google Scholar 

  • Zografos, K., Douligeris, C. and C. Lin, A Model for the Optimum Deployment of Emergency Repair Trucks: An Application in the Electric Utility Industry, Transportation Research Record, 1358, pp. 88-94 (1992).

    Google Scholar 

  • Zografos, K., Douligeris, C., and C. Lin, A Simulation Model for Evaluating the Performance of an Emergency Response Fleet, Transportation Research Record, 1452, pp. 27-34 (1994)

    Google Scholar 

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Haghani, A., Yang, S. (2007). Real-Time Emergency Response Fleet Deployment: Concepts, Systems, Simulation & Case Studies. In: Zeimpekis, V., Tarantilis, C.D., Giaglis, G.M., Minis, I. (eds) Dynamic Fleet Management. Operations Research/Computer Science Interfaces Series, vol 38. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-71722-7_7

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