How to cite this paper
Roa, J., Escobar, J & Moreno, C. (2020). An online real-time matheuristic algorithm for dispatch and relocation of ambulances.International Journal of Industrial Engineering Computations , 11(3), 443-468.
References
Andersson, T., & Värbrand, P. (2007). Decision support tools for ambulance dispatch and relocation. Journal of the Operational Research Society, 58(2), 195-201.
Aringhieri, R., Bruni, M. E., Khodaparasti, S., & van Essen, J. T. (2017). Emergency medical services and beyond: Addressing new challenges through a wide literature review. Computers & Operations Research, 78, 349-368.
Aringhieri, R., Bocca, S., Casciaro, L., & Duma, D. (2018). A simulation and online optimization approach for the real-time management of ambulances. In Proceedings of the 2018 Winter Simulation Conference (pp. 2554-2565). IEEE Press.
Bagherinejad, J., & Shoeib, M. (2018). Dynamic capacitated maximal covering location problem by considering dynamic capacity. International Journal of Industrial Engineering Computations, 9(2), 249-264.
Başar, A., Çatay, B., & Ünlüyurt, T. (2012). A taxonomy for emergency service station location problem. Optimization letters, 6(6), 1147-1160.
Bélanger, V., Ruiz, A., Soriano, P., & Lanzarone, E. (2015). The ambulance relocation and dispatching problem. CIRRELT.
Bélanger, V., Kergosien, Y., Ruiz, A., & Soriano, P. (2016). An empirical comparison of relocation strategies in real-time ambulance fleet management. Computers & Industrial Engineering, 94, 216-229.
Bélanger, V., Ruiz, A., & Soriano, P. (2019). Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles. European Journal of Operational Research, 272(1), 1-23.
Daskin, M. S. (1983). A maximum expected covering location model: formulation, properties and heuristic solution. Transportation science, 17(1), 48-70.
Enayati, S., Mayorga, M. E., Rajagopalan, H. K., & Saydam, C. (2018, a). Real-time ambulance redeployment approach to improve service coverage with fair and restricted workload for EMS providers. Omega, 79, 67-80.
Enayati, S., Özaltın, O. Y., Mayorga, M. E., & Saydam, C. (2018, b). Ambulance redeployment and dispatching under uncertainty with personnel workload limitations. IISE Transactions, 50(9), 777-788.
Enayati, S., Mayorga, M. E., Toro‐Díaz, H., & Albert, L. A. (2019). Identifying trade‐offs in equity and efficiency for simultaneously optimizing location and multipriority dispatch of ambulances. International Transactions in Operational Research, 26(2), 415-438.
Gendreau, M., Laporte, G., & Semet, F. (1997). Solving an ambulance location model by tabu search. Location Science, 5(2), 75-88.
Gendreau, M., Laporte, G., & Semet, F. (2001). A dynamic model and parallel tabu search heuristic for real-time ambulance relocation. Parallel computing, 27(12), 1641-1653.
Goldberg, J. B. (2004). Operations research models for the deployment of emergency services vehicles. EMS management Journal, 1(1), 20-39.
Haghani, A., & Yang, S. (2007). Real-time emergency response fleet deployment: Concepts, systems, simulation & case studies. In Dynamic fleet management (pp. 133-162). Springer, Boston, MA.
Hakimi, S. L. (1964). Optimum locations of switching centers and the absolute centers and medians of a graph. Operations research, 12(3), 450-459.
Jagtenberg, C. J., Bhulai, S., & Van der Mei, R. D. (2015). An efficient heuristic for real-time ambulance redeployment. Operations Research for Health Care, 4, 27-35.
Karimi, A., Gendreau, M., & Verter, V. (2018). Performance Approximation of Emergency Service Systems with Priorities and Partial Backups. Transportation Science, 52(5), 1235-1252.
Kergosien, Y., Bélanger, V., Soriano, P., Gendreau, M., & Ruiz, A. (2015). A generic and flexible simulation-based analysis tool for EMS management. International Journal of Production Research, 53(24), 7299-7316.
Lee, S. (2011). The role of preparedness in ambulance dispatching. Journal of the Operational Research Society, 62(10), 1888-1897.
Maxwell, M. S., Restrepo, M., Henderson, S. G., & Topaloglu, H. (2010). Approximate dynamic programming for ambulance redeployment. INFORMS Journal on Computing, 22(2), 266-281.
Maxwell, M. S., Henderson, S. G., & Topaloglu, H. (2013). Tuning approximate dynamic programming policies for ambulance redeployment via direct search. Stochastic Systems, 3(2), 322-361.
Maxwell, M. S., Ni, E. C., Tong, C., Henderson, S. G., Topaloglu, H., & Hunter, S. R. (2014). A bound on the performance of an optimal ambulance redeployment policy. Operations Research, 62(5), 1014-1027.
McCormack, R., & Coates, G. (2015). A simulation model to enable the optimization of ambulance fleet allocation and base station location for increased patient survival. European Journal of Operational Research, 247(1), 294-309.
Nasrollahzadeh, A. A., Khademi, A., & Mayorga, M. E. (2018). Real-time ambulance dispatching and relocation. Manufacturing & Service Operations Management, 20(3), 467-480.
Pinto, L. R., Silva, P. M., et al. (2015). A generic method to develop simulation models for ambulance systems. Simulation Modelling Practice and Theory, 51, 170-183.
Schmid, V. (2012). Solving the dynamic ambulance relocation and dispatching problem using approximate dynamic programming. European Journal of Operational Research, 219(3), 611-621.
Sudtachat, K., Mayorga, M. E., & Mclay, L. A. (2016). A nested-compliance table policy for emergency medical service systems under relocation. Omega, 58, 154-168.
Sung, I., & Lee, T. (2018). Scenario-based approach for the ambulance location problem with stochastic call arrivals under a dispatching policy. Flexible Services and Manufacturing Journal, 30(1-2), 153-170.
van Barneveld, T. C., Bhulai, S., & van der Mei, R. D. (2016). The effect of ambulance relocations on the performance of ambulance service providers. European Journal of Operational Research, 252(1), 257-269.
van Barneveld, T. C., Bhulai, S., & van der Mei, R. D. (2017, a). A dynamic ambulance management model for rural areas. Health care Management Science, 20(2), 165-186.
van Barneveld, T. C., van der Mei, R. D., & Bhulai, S. (2017, b). Compliance tables for an EMS system with two types of medical response units. Computers & Operations Research, 80, 68-81.
van Barneveld, T., Jagtenberg, C., Bhulai, S., & van der Mei, R. (2018). Real-time ambulance relocation: Assessing real-time redeployment strategies for ambulance relocation. Socio-Economic Planning Sciences, 62, 129-142.
van den Berg, P. L., Fiskerstrand, P., Aardal, K., Einerkjær, J., Thoresen, T., & Røislien, J. (2019). Improving ambulance coverage in a mixed urban-rural region in Norway using mathematical modeling. PloS one, 14(4), e0215385.
Aringhieri, R., Bruni, M. E., Khodaparasti, S., & van Essen, J. T. (2017). Emergency medical services and beyond: Addressing new challenges through a wide literature review. Computers & Operations Research, 78, 349-368.
Aringhieri, R., Bocca, S., Casciaro, L., & Duma, D. (2018). A simulation and online optimization approach for the real-time management of ambulances. In Proceedings of the 2018 Winter Simulation Conference (pp. 2554-2565). IEEE Press.
Bagherinejad, J., & Shoeib, M. (2018). Dynamic capacitated maximal covering location problem by considering dynamic capacity. International Journal of Industrial Engineering Computations, 9(2), 249-264.
Başar, A., Çatay, B., & Ünlüyurt, T. (2012). A taxonomy for emergency service station location problem. Optimization letters, 6(6), 1147-1160.
Bélanger, V., Ruiz, A., Soriano, P., & Lanzarone, E. (2015). The ambulance relocation and dispatching problem. CIRRELT.
Bélanger, V., Kergosien, Y., Ruiz, A., & Soriano, P. (2016). An empirical comparison of relocation strategies in real-time ambulance fleet management. Computers & Industrial Engineering, 94, 216-229.
Bélanger, V., Ruiz, A., & Soriano, P. (2019). Recent optimization models and trends in location, relocation, and dispatching of emergency medical vehicles. European Journal of Operational Research, 272(1), 1-23.
Daskin, M. S. (1983). A maximum expected covering location model: formulation, properties and heuristic solution. Transportation science, 17(1), 48-70.
Enayati, S., Mayorga, M. E., Rajagopalan, H. K., & Saydam, C. (2018, a). Real-time ambulance redeployment approach to improve service coverage with fair and restricted workload for EMS providers. Omega, 79, 67-80.
Enayati, S., Özaltın, O. Y., Mayorga, M. E., & Saydam, C. (2018, b). Ambulance redeployment and dispatching under uncertainty with personnel workload limitations. IISE Transactions, 50(9), 777-788.
Enayati, S., Mayorga, M. E., Toro‐Díaz, H., & Albert, L. A. (2019). Identifying trade‐offs in equity and efficiency for simultaneously optimizing location and multipriority dispatch of ambulances. International Transactions in Operational Research, 26(2), 415-438.
Gendreau, M., Laporte, G., & Semet, F. (1997). Solving an ambulance location model by tabu search. Location Science, 5(2), 75-88.
Gendreau, M., Laporte, G., & Semet, F. (2001). A dynamic model and parallel tabu search heuristic for real-time ambulance relocation. Parallel computing, 27(12), 1641-1653.
Goldberg, J. B. (2004). Operations research models for the deployment of emergency services vehicles. EMS management Journal, 1(1), 20-39.
Haghani, A., & Yang, S. (2007). Real-time emergency response fleet deployment: Concepts, systems, simulation & case studies. In Dynamic fleet management (pp. 133-162). Springer, Boston, MA.
Hakimi, S. L. (1964). Optimum locations of switching centers and the absolute centers and medians of a graph. Operations research, 12(3), 450-459.
Jagtenberg, C. J., Bhulai, S., & Van der Mei, R. D. (2015). An efficient heuristic for real-time ambulance redeployment. Operations Research for Health Care, 4, 27-35.
Karimi, A., Gendreau, M., & Verter, V. (2018). Performance Approximation of Emergency Service Systems with Priorities and Partial Backups. Transportation Science, 52(5), 1235-1252.
Kergosien, Y., Bélanger, V., Soriano, P., Gendreau, M., & Ruiz, A. (2015). A generic and flexible simulation-based analysis tool for EMS management. International Journal of Production Research, 53(24), 7299-7316.
Lee, S. (2011). The role of preparedness in ambulance dispatching. Journal of the Operational Research Society, 62(10), 1888-1897.
Maxwell, M. S., Restrepo, M., Henderson, S. G., & Topaloglu, H. (2010). Approximate dynamic programming for ambulance redeployment. INFORMS Journal on Computing, 22(2), 266-281.
Maxwell, M. S., Henderson, S. G., & Topaloglu, H. (2013). Tuning approximate dynamic programming policies for ambulance redeployment via direct search. Stochastic Systems, 3(2), 322-361.
Maxwell, M. S., Ni, E. C., Tong, C., Henderson, S. G., Topaloglu, H., & Hunter, S. R. (2014). A bound on the performance of an optimal ambulance redeployment policy. Operations Research, 62(5), 1014-1027.
McCormack, R., & Coates, G. (2015). A simulation model to enable the optimization of ambulance fleet allocation and base station location for increased patient survival. European Journal of Operational Research, 247(1), 294-309.
Nasrollahzadeh, A. A., Khademi, A., & Mayorga, M. E. (2018). Real-time ambulance dispatching and relocation. Manufacturing & Service Operations Management, 20(3), 467-480.
Pinto, L. R., Silva, P. M., et al. (2015). A generic method to develop simulation models for ambulance systems. Simulation Modelling Practice and Theory, 51, 170-183.
Schmid, V. (2012). Solving the dynamic ambulance relocation and dispatching problem using approximate dynamic programming. European Journal of Operational Research, 219(3), 611-621.
Sudtachat, K., Mayorga, M. E., & Mclay, L. A. (2016). A nested-compliance table policy for emergency medical service systems under relocation. Omega, 58, 154-168.
Sung, I., & Lee, T. (2018). Scenario-based approach for the ambulance location problem with stochastic call arrivals under a dispatching policy. Flexible Services and Manufacturing Journal, 30(1-2), 153-170.
van Barneveld, T. C., Bhulai, S., & van der Mei, R. D. (2016). The effect of ambulance relocations on the performance of ambulance service providers. European Journal of Operational Research, 252(1), 257-269.
van Barneveld, T. C., Bhulai, S., & van der Mei, R. D. (2017, a). A dynamic ambulance management model for rural areas. Health care Management Science, 20(2), 165-186.
van Barneveld, T. C., van der Mei, R. D., & Bhulai, S. (2017, b). Compliance tables for an EMS system with two types of medical response units. Computers & Operations Research, 80, 68-81.
van Barneveld, T., Jagtenberg, C., Bhulai, S., & van der Mei, R. (2018). Real-time ambulance relocation: Assessing real-time redeployment strategies for ambulance relocation. Socio-Economic Planning Sciences, 62, 129-142.
van den Berg, P. L., Fiskerstrand, P., Aardal, K., Einerkjær, J., Thoresen, T., & Røislien, J. (2019). Improving ambulance coverage in a mixed urban-rural region in Norway using mathematical modeling. PloS one, 14(4), e0215385.