How to cite this paper
Karimi, M., Mohammadi, E., Jafari, H., Ghaeli, M & Eskoruchi, A. (2022). A robust linear model for the maximum expected coverage location problem considering the relative coverage.Journal of Future Sustainability, 2(2), 39-48.
Refrences
Adarang, H., Bozorgi-Amiri, A., Khalili-Damghani, K., & Tavakkoli-Moghaddam, R. (2020). A robust bi-objective lo-cation-routing model for providing emergency medical services. Journal of Humanitarian Logistics and Supply Chain Management, 10(3), 285-319.
Ansari, S., McLay, L. A., & Mayorga, M. E. (2015). A maximum expected covering problem for district design. Transportation Science, 51(1), 376-390.
Bertsimas, D., & Sim, M. (2003). Robust discrete optimization and network flows. Mathematical programming, 98(1), 49-71.
Bertsimas, D., & Sim, M. (2004). The price of robustness. Operations research, 52(1), 35-53.
Boutilier, J.J., Chan, T.C.Y. (2020). Ambulance emergency response optimization in developing countries. Operations Research, 65(5), 1315-1334.
Church, R., & ReVelle, C. (1974). The maximal covering location problem. Papers of the Regional Science Association, 32(1), 101-118.
Daskin, M. S. (1983). A maximum expected covering location model: formulation, properties and heuristic solution. Transportation science, 17(1), 48-70.
Fujiwara, O., Kachenchai, K., Makjamroen, T., & Gupta, K. (1988). An efficient scheme for deployment of ambulances in metropolitan Bangkok. Operational research, 87, 730-741.
Fujiwara, O., Makjamroen, T., & Gupta, K. K. (1987). Ambulance deployment analysis: a case study of Bangkok. European Journal of Operational Research, 31(1), 9-18
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.
Jenkins, P.R., Lunday, B.J., & Robbims, M.J. (2020). Robust, multi-objective optimization for the military medical evacuation location-allocation problem. Omega, 97,102088.
Lam, S. S. W., Ng, Y. S., Lakshmanan, M. R., Ng, Y. Y., & Ong, M. E. H. (2016). Ambulance deployment under demand uncertainty. Journal of Advanced Management Science, 4(3).
Maleki, M., Majlesinasab, N., & Sepehri, M. M. (2014). Two new models for redeployment of ambulances. Computers & Industrial Engineering, 78, 271-284.
Rajagopalan, H. K., Saydam, C., & Xiao, J. (2008). A multiperiod set covering location model for dynamic redeployment of ambulances. Computers & Operations Research, 35(3), 814-826.
Rajagopalan, H. K., Vergara, F. E., Saydam, C., & Xiao, J. (2007). Developing effective meta-heuristics for a probabilistic location model via experimental design. European Journal of Operational Research, 177(1), 83-101.
ReVelle, C., & Hogan, K. (1989). The maximum availability location problem. Transportation Science, 23(3), 192-200.
Rojas-Trejos, C. A., González-Velasco, J., & López-Ramírez, M. A. (2017). Optimization Model for the Location of Prehospital Care Ambulances in the city of Cali Colombia. International Journal of Combinatorial Optimization Problems and Informatics, 8(3), 64-70.
Saydam, C., & McKnew, M. (1985). Applications and implementation a separable programming approach to expected coverage: An application to ambulance location. Decision Sciences, 16(4), 381-398.
Sorensen, P., & Church, R. (2010). Integrating expected coverage and local reliability for emergency medical services location problems. Socio-Economic Planning Sciences, 44(1), 8-18
Sun, H., Wang, Y., Xue, Y. (2021a). A bi-objective robust optimization model for disaster response planning under un-certainties. Computers and Industrial Engineering, 155, 107213.
Sun, H., Wang, Y., Zhang, J., Cao, W. (2021b). A robust optimization model for location-transportation problem of dis-aster casualties with triage and uncertainty. Expert Systems with Applications, 175, 114867.
Toregas, C., Swain, R., ReVelle, C., & Bergman, L. (1971). The location of emergency service facilities. Operations research, 19(6), 1363-1373.
Trujillo, L., Álvarez-Hernández, G., Maldonado, Y., Vera, C. (2020). Comparative analysis of relocation strategies for ambulances in the city of Tijuana, Mexico. Computers in Biology and Medicine, 116, 103567.
Van den Berg, P. L., & Aardal, K. (2015). Time-dependent MEXCLP with start-up and relocation cost. European Journal of Operational Research, 242(2), 383-389.
Van den Berg, P. L., Kommer, G. J., & Zuzáková, B. (2016). Linear formulation for the maximum expected coverage location model with fractional coverage. Operations Research for Health Care, 8, 33-41
Zhang, R., & Zheng, B.(2019). Ambulance deployment with relocation through robust optimization. IEEE Transactions on Automation Science and Engineering, 16(1), 138-147.
Zhang, Z. H., & Jiang, H. (2014). A robust counterpart approach to the bi-objective emergency medical service design problem. Applied Mathematical Modelling, 38(3), 1033-1040.
Ansari, S., McLay, L. A., & Mayorga, M. E. (2015). A maximum expected covering problem for district design. Transportation Science, 51(1), 376-390.
Bertsimas, D., & Sim, M. (2003). Robust discrete optimization and network flows. Mathematical programming, 98(1), 49-71.
Bertsimas, D., & Sim, M. (2004). The price of robustness. Operations research, 52(1), 35-53.
Boutilier, J.J., Chan, T.C.Y. (2020). Ambulance emergency response optimization in developing countries. Operations Research, 65(5), 1315-1334.
Church, R., & ReVelle, C. (1974). The maximal covering location problem. Papers of the Regional Science Association, 32(1), 101-118.
Daskin, M. S. (1983). A maximum expected covering location model: formulation, properties and heuristic solution. Transportation science, 17(1), 48-70.
Fujiwara, O., Kachenchai, K., Makjamroen, T., & Gupta, K. (1988). An efficient scheme for deployment of ambulances in metropolitan Bangkok. Operational research, 87, 730-741.
Fujiwara, O., Makjamroen, T., & Gupta, K. K. (1987). Ambulance deployment analysis: a case study of Bangkok. European Journal of Operational Research, 31(1), 9-18
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.
Jenkins, P.R., Lunday, B.J., & Robbims, M.J. (2020). Robust, multi-objective optimization for the military medical evacuation location-allocation problem. Omega, 97,102088.
Lam, S. S. W., Ng, Y. S., Lakshmanan, M. R., Ng, Y. Y., & Ong, M. E. H. (2016). Ambulance deployment under demand uncertainty. Journal of Advanced Management Science, 4(3).
Maleki, M., Majlesinasab, N., & Sepehri, M. M. (2014). Two new models for redeployment of ambulances. Computers & Industrial Engineering, 78, 271-284.
Rajagopalan, H. K., Saydam, C., & Xiao, J. (2008). A multiperiod set covering location model for dynamic redeployment of ambulances. Computers & Operations Research, 35(3), 814-826.
Rajagopalan, H. K., Vergara, F. E., Saydam, C., & Xiao, J. (2007). Developing effective meta-heuristics for a probabilistic location model via experimental design. European Journal of Operational Research, 177(1), 83-101.
ReVelle, C., & Hogan, K. (1989). The maximum availability location problem. Transportation Science, 23(3), 192-200.
Rojas-Trejos, C. A., González-Velasco, J., & López-Ramírez, M. A. (2017). Optimization Model for the Location of Prehospital Care Ambulances in the city of Cali Colombia. International Journal of Combinatorial Optimization Problems and Informatics, 8(3), 64-70.
Saydam, C., & McKnew, M. (1985). Applications and implementation a separable programming approach to expected coverage: An application to ambulance location. Decision Sciences, 16(4), 381-398.
Sorensen, P., & Church, R. (2010). Integrating expected coverage and local reliability for emergency medical services location problems. Socio-Economic Planning Sciences, 44(1), 8-18
Sun, H., Wang, Y., Xue, Y. (2021a). A bi-objective robust optimization model for disaster response planning under un-certainties. Computers and Industrial Engineering, 155, 107213.
Sun, H., Wang, Y., Zhang, J., Cao, W. (2021b). A robust optimization model for location-transportation problem of dis-aster casualties with triage and uncertainty. Expert Systems with Applications, 175, 114867.
Toregas, C., Swain, R., ReVelle, C., & Bergman, L. (1971). The location of emergency service facilities. Operations research, 19(6), 1363-1373.
Trujillo, L., Álvarez-Hernández, G., Maldonado, Y., Vera, C. (2020). Comparative analysis of relocation strategies for ambulances in the city of Tijuana, Mexico. Computers in Biology and Medicine, 116, 103567.
Van den Berg, P. L., & Aardal, K. (2015). Time-dependent MEXCLP with start-up and relocation cost. European Journal of Operational Research, 242(2), 383-389.
Van den Berg, P. L., Kommer, G. J., & Zuzáková, B. (2016). Linear formulation for the maximum expected coverage location model with fractional coverage. Operations Research for Health Care, 8, 33-41
Zhang, R., & Zheng, B.(2019). Ambulance deployment with relocation through robust optimization. IEEE Transactions on Automation Science and Engineering, 16(1), 138-147.
Zhang, Z. H., & Jiang, H. (2014). A robust counterpart approach to the bi-objective emergency medical service design problem. Applied Mathematical Modelling, 38(3), 1033-1040.