How to cite this paper
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.
Refrences
Beasley, J. E., & Chu, P. C. (1996). A genetic algorithm for the set covering problem. European Journal of Operational Research, 94(2), 392–404.
Berlin, G. N., & Liebman, J. C. (1974). Mathematical analysis of emergency ambulance location. Socio-Economic Planning Sciences, 8(6), 323–328.
Boloori Arabani, A., & Zanjirani Farahani, R. (2012). Facility location dynamics: An overview of classifications and applications. Computers & Industrial Engineering, 62(1), 408–420.
Canel, C., Khumawala, B. M., Law, J., & Loh, A. (2001). An algorithm for the capacitated , multi-commodity multi-period facility location problem. Computer & Operation Research, 28(5), 411–427.
Chan, K. Y., Rajakaruna, N., Engelke, U., Murray, I., & Abhayasinghe, N. (2015). Alignment parameter calibration for IMU using the Taguchi method for image deblurring. Measurement, 65(Apr 2015), 207-219.
Church, R., & Revelle, C. (1974). The maximal covering location problem. Papers in Regional Science, 32(1), 101–118.
Correia, I., & Captivo, M. E. (2003). A lagrangean heuristic for a modular capacitated location problem. Annal of Opeation Research, 122(1-4), 141–161.
Correia, I., & Captivo, M. E. (2006). Bounds for the single source modular capacitated plant location problem. Computers & Operations Research, 33(10), 2991–3003.
Current, J. R., & Storbeck, J. E. (1988). Capacitated covering models. Environment and Planning B: Planning and Design, 15(2), 153–163.
Current, J., Ratick, S., & Revelle, C. (1998). Dynamic facility location when the total number of facilities is uncertain: A decision analysis approach. European Journal of Operational Research, 110(3), 597–609.
Daskin, M. S., Hopp, W. J., & Medina, B. (1992). Forecast horizons and dynamic facility location planning. Annals of Operations Research, 40(1), 125–151.
Datta, S. (2012). Multi-criteria multi-facility location in Niwai block, Rajasthan. IIMB Management Review, 24(1), 16–27.
Davari, S., Fazel Zarandi, M. H., & Turksen, I. B. (2013). A greedy variable neighborhood search heuristic for the maximal covering location problem with fuzzy coverage radii. Knowledge-Based Systems, 41(March 2013), 68–76.
Dell’Olmo, P., Ricciardi, N., & Sgalambro, A. (2014). A multiperiod maximal covering location model for the optimal location of intersection safety cameras on an urban traffi0c network. Procedia-Social and Behavioral Sciences, 108, 106–117.
Fallah, H., Naimi Sadigh, A., & Aslanzadeh, M. (2009). Covering problem, in: Zanjirani Farahani, R., & Hekmatfar, M. (Eds.), Facility Location: Concepts, Models, Algorithms and Case studies. Berlin: Springer-Verlag , pp. 145-176.
Fazel Zarandi, M. H., Davari, S., & Haddad Sisakht, S. A. (2013). The large-scale dynamic maximal covering location problem. Mathematical and Computer Modelling, 57(3), 710–719.
Griffin, P. M., Scherrer, C. R., & Swann, J. L. (2008). Optimization of community health center locations and service offerings with statistical need estimation. IIE Transactions, 40(9), 880–892.
Haghani, A. (1996). Capacitated maximum covering location models: Formulations and solution procedures. Journal of Advanced Transportation, 30(3), 101–136.
Hakimi, S. L. (1965). Optimum distribution of switching centers in a communication network and some related graph theoretic problems. Operations Research, 13(3), 462-475.
Holland, J. H. (1975). Adaptation in natural and artificial systems: An introductory analysis with application to biology, control, and artificial intelligence. Ann Arbor: University of Michigan Press.
Hormozi, A. M., & Khumawala, B. M. (1996). An improved algorithm for solving a multi-period facility location problem. IIE transactions, 28(2), 105-114.
Jahantigh, F. F., & Malmir, B. (2016, March). A Hybrid Genetic Algorithm for Solving Facility Location Allocation Problem. In Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management, Kuala Lumpur, Malaysia.
Jaramillo, J. H., Bhadury, J., & Batta, R. (2002). On the use of genetic algorithms to solve location problems. Computers & Operations Research, 29(6), 761–779.
Köksoy, O., & Yalcinoz, T. (2008). Robust design using pareto type optimization: A genetic algorithm with arithmetic crossover. Computers & Industrial Engineering, 55(1), 208–218.
Liao, A., & Approach, D. G. (2008). A clustering-based approach to the capacitated facility location problem. Transactions in GIS, 12(3), 323–339.
Matthias, K., Severin, T., & Salzwedel, H. (2013). Variable mutation rate at genetic algorithms: Introduction of chromosome fitness in connection with multi-chromosome representation. International Journal of Computer Applications, 72(17), 31–38.
Máximo, V. R., Nascimento, M. C., & Carvalho, A. C. (2017). Intelligent guided adaptive search for the maximum covering location problem. Computers & Operations Research, 78(Feb 2017), 129–137.
Mehdizadeh, E., & Afrabandpei, F. (2012). Design of a mathematical model for logistic network in a multi-stage multi-product supply chain network and developing a metaheuristic algorithm. Journal of Optimization in Industrial Engineering, 5(10), 35–43.
Miller, T. C., Friesz, T. L., Tobin, R. L., & Kwon, C. (2006). Reaction function based dynamic location modeling in Stackelberg–Nash–Cournot competition. Networks and Spatial Economics, 7(1), 77–97.
Murray, T., & Gerrard, R. A. (1998). Capacitated service and regional constraints in location-allocation modeling. Location Science, 5(2), 103–118.
Niroomand, I. (2008). Modeling and analysis of the generalized warehouse location problem with staircase costs (Doctoral dissertation, Concordia University Montreal, Quebec, Canada).
Pasandideh, S. H. R., Akhavan Niaki, S. T., & Asadi, K. (2015). Bi-objective optimization of a multi-product multi-period three-echelon supply chain problem under uncertain environments: NSGA-II and NRGA. Information Sciences, 292(Jan 2015), 57–74.
Pham, D. T., Ghanbarzadeh, A., Koc, E., Otri, S., Rahim, S., & Zaidi, M. (2011, July). The bees algorithm-A novel tool for complex optimisation. In Intelligent Production Machines and Systems-2nd I* PROMS Virtual International Conference (3-14 July 2006). sn.
Pirkul, H., & Schilling, D. (1989). The capacitated maximal covering location problem with backup service. Annal of Opeation Research, 18(1), 141–154.
Pirkul, H., & Schilling, D. A. (1991). The maximal covering location problem with capacities on total workload. Management Science, 37(2), 233–248.
Raju, B. S., Shekar, U. C., Venkateswarlu, K., & Drakashayani, D. N. (2014). Establishment of Process model for rapid prototyping technique (Stereolithography) to enhance the part quality by Taguchi method. Procedia Technology, 14(Jan 2014), 380–389.
Revelle, C., Scholssberg, M., & Williams, J. (2008). Solving the maximal covering location problem with heuristic concentration. Computers & Operations Research, 35(2), 427–435.
Salari, M. (2013). An iterated local search for the budget constrained generalized maximal covering location problem. Journal of Mathematical Modelling and Algorithms in Operations Research, 13(3), 301–313.
Schilling, D. A. (1980). Dynamic location modeling for public-sector facilities: A multicriteria approach. Decision Sciences, 11(4), 714–724.
Schilling, D. A., Jayaraman, V., & Barkhi, R. (1993). A review of covering problem in facility location. Location Science, 1(1), 25–55.
Toregas, C., Swain, R., ReVelle, C., & Bergman, L. (1971). The location of emergency service facilities. Operations Research, 19(6), 1363-1373.
Tsai, H. (2014). Novel bees algorithm: Stochastic self-adaptive neighborhood. Applied Mathematics and Computation, 247(Nov 2014), 1161–1172.
Vatsa, A. K., & Jayaswal, S. (2016). A new formulation and Benders decomposition for the multi-period maximal covering facility location problem with server uncertainty. European Journal of Operational Research, 251(2), 404-418.
Yin, P., & Mu, L. (2012). Modular capacitated maximal covering location problem for the optimal siting of emergency vehicles. Applied Geography, 34(May 2012), 247–254.
Zanjirani Farahani, R., & Hekmatfar, M. (2009). Facility location: Concept, Models, Algorithms and Case Studies. Heidelberg: Physica-Verlag.
Berlin, G. N., & Liebman, J. C. (1974). Mathematical analysis of emergency ambulance location. Socio-Economic Planning Sciences, 8(6), 323–328.
Boloori Arabani, A., & Zanjirani Farahani, R. (2012). Facility location dynamics: An overview of classifications and applications. Computers & Industrial Engineering, 62(1), 408–420.
Canel, C., Khumawala, B. M., Law, J., & Loh, A. (2001). An algorithm for the capacitated , multi-commodity multi-period facility location problem. Computer & Operation Research, 28(5), 411–427.
Chan, K. Y., Rajakaruna, N., Engelke, U., Murray, I., & Abhayasinghe, N. (2015). Alignment parameter calibration for IMU using the Taguchi method for image deblurring. Measurement, 65(Apr 2015), 207-219.
Church, R., & Revelle, C. (1974). The maximal covering location problem. Papers in Regional Science, 32(1), 101–118.
Correia, I., & Captivo, M. E. (2003). A lagrangean heuristic for a modular capacitated location problem. Annal of Opeation Research, 122(1-4), 141–161.
Correia, I., & Captivo, M. E. (2006). Bounds for the single source modular capacitated plant location problem. Computers & Operations Research, 33(10), 2991–3003.
Current, J. R., & Storbeck, J. E. (1988). Capacitated covering models. Environment and Planning B: Planning and Design, 15(2), 153–163.
Current, J., Ratick, S., & Revelle, C. (1998). Dynamic facility location when the total number of facilities is uncertain: A decision analysis approach. European Journal of Operational Research, 110(3), 597–609.
Daskin, M. S., Hopp, W. J., & Medina, B. (1992). Forecast horizons and dynamic facility location planning. Annals of Operations Research, 40(1), 125–151.
Datta, S. (2012). Multi-criteria multi-facility location in Niwai block, Rajasthan. IIMB Management Review, 24(1), 16–27.
Davari, S., Fazel Zarandi, M. H., & Turksen, I. B. (2013). A greedy variable neighborhood search heuristic for the maximal covering location problem with fuzzy coverage radii. Knowledge-Based Systems, 41(March 2013), 68–76.
Dell’Olmo, P., Ricciardi, N., & Sgalambro, A. (2014). A multiperiod maximal covering location model for the optimal location of intersection safety cameras on an urban traffi0c network. Procedia-Social and Behavioral Sciences, 108, 106–117.
Fallah, H., Naimi Sadigh, A., & Aslanzadeh, M. (2009). Covering problem, in: Zanjirani Farahani, R., & Hekmatfar, M. (Eds.), Facility Location: Concepts, Models, Algorithms and Case studies. Berlin: Springer-Verlag , pp. 145-176.
Fazel Zarandi, M. H., Davari, S., & Haddad Sisakht, S. A. (2013). The large-scale dynamic maximal covering location problem. Mathematical and Computer Modelling, 57(3), 710–719.
Griffin, P. M., Scherrer, C. R., & Swann, J. L. (2008). Optimization of community health center locations and service offerings with statistical need estimation. IIE Transactions, 40(9), 880–892.
Haghani, A. (1996). Capacitated maximum covering location models: Formulations and solution procedures. Journal of Advanced Transportation, 30(3), 101–136.
Hakimi, S. L. (1965). Optimum distribution of switching centers in a communication network and some related graph theoretic problems. Operations Research, 13(3), 462-475.
Holland, J. H. (1975). Adaptation in natural and artificial systems: An introductory analysis with application to biology, control, and artificial intelligence. Ann Arbor: University of Michigan Press.
Hormozi, A. M., & Khumawala, B. M. (1996). An improved algorithm for solving a multi-period facility location problem. IIE transactions, 28(2), 105-114.
Jahantigh, F. F., & Malmir, B. (2016, March). A Hybrid Genetic Algorithm for Solving Facility Location Allocation Problem. In Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management, Kuala Lumpur, Malaysia.
Jaramillo, J. H., Bhadury, J., & Batta, R. (2002). On the use of genetic algorithms to solve location problems. Computers & Operations Research, 29(6), 761–779.
Köksoy, O., & Yalcinoz, T. (2008). Robust design using pareto type optimization: A genetic algorithm with arithmetic crossover. Computers & Industrial Engineering, 55(1), 208–218.
Liao, A., & Approach, D. G. (2008). A clustering-based approach to the capacitated facility location problem. Transactions in GIS, 12(3), 323–339.
Matthias, K., Severin, T., & Salzwedel, H. (2013). Variable mutation rate at genetic algorithms: Introduction of chromosome fitness in connection with multi-chromosome representation. International Journal of Computer Applications, 72(17), 31–38.
Máximo, V. R., Nascimento, M. C., & Carvalho, A. C. (2017). Intelligent guided adaptive search for the maximum covering location problem. Computers & Operations Research, 78(Feb 2017), 129–137.
Mehdizadeh, E., & Afrabandpei, F. (2012). Design of a mathematical model for logistic network in a multi-stage multi-product supply chain network and developing a metaheuristic algorithm. Journal of Optimization in Industrial Engineering, 5(10), 35–43.
Miller, T. C., Friesz, T. L., Tobin, R. L., & Kwon, C. (2006). Reaction function based dynamic location modeling in Stackelberg–Nash–Cournot competition. Networks and Spatial Economics, 7(1), 77–97.
Murray, T., & Gerrard, R. A. (1998). Capacitated service and regional constraints in location-allocation modeling. Location Science, 5(2), 103–118.
Niroomand, I. (2008). Modeling and analysis of the generalized warehouse location problem with staircase costs (Doctoral dissertation, Concordia University Montreal, Quebec, Canada).
Pasandideh, S. H. R., Akhavan Niaki, S. T., & Asadi, K. (2015). Bi-objective optimization of a multi-product multi-period three-echelon supply chain problem under uncertain environments: NSGA-II and NRGA. Information Sciences, 292(Jan 2015), 57–74.
Pham, D. T., Ghanbarzadeh, A., Koc, E., Otri, S., Rahim, S., & Zaidi, M. (2011, July). The bees algorithm-A novel tool for complex optimisation. In Intelligent Production Machines and Systems-2nd I* PROMS Virtual International Conference (3-14 July 2006). sn.
Pirkul, H., & Schilling, D. (1989). The capacitated maximal covering location problem with backup service. Annal of Opeation Research, 18(1), 141–154.
Pirkul, H., & Schilling, D. A. (1991). The maximal covering location problem with capacities on total workload. Management Science, 37(2), 233–248.
Raju, B. S., Shekar, U. C., Venkateswarlu, K., & Drakashayani, D. N. (2014). Establishment of Process model for rapid prototyping technique (Stereolithography) to enhance the part quality by Taguchi method. Procedia Technology, 14(Jan 2014), 380–389.
Revelle, C., Scholssberg, M., & Williams, J. (2008). Solving the maximal covering location problem with heuristic concentration. Computers & Operations Research, 35(2), 427–435.
Salari, M. (2013). An iterated local search for the budget constrained generalized maximal covering location problem. Journal of Mathematical Modelling and Algorithms in Operations Research, 13(3), 301–313.
Schilling, D. A. (1980). Dynamic location modeling for public-sector facilities: A multicriteria approach. Decision Sciences, 11(4), 714–724.
Schilling, D. A., Jayaraman, V., & Barkhi, R. (1993). A review of covering problem in facility location. Location Science, 1(1), 25–55.
Toregas, C., Swain, R., ReVelle, C., & Bergman, L. (1971). The location of emergency service facilities. Operations Research, 19(6), 1363-1373.
Tsai, H. (2014). Novel bees algorithm: Stochastic self-adaptive neighborhood. Applied Mathematics and Computation, 247(Nov 2014), 1161–1172.
Vatsa, A. K., & Jayaswal, S. (2016). A new formulation and Benders decomposition for the multi-period maximal covering facility location problem with server uncertainty. European Journal of Operational Research, 251(2), 404-418.
Yin, P., & Mu, L. (2012). Modular capacitated maximal covering location problem for the optimal siting of emergency vehicles. Applied Geography, 34(May 2012), 247–254.
Zanjirani Farahani, R., & Hekmatfar, M. (2009). Facility location: Concept, Models, Algorithms and Case Studies. Heidelberg: Physica-Verlag.