[1] Current, J.R., Daskin, M.S., Schilling, D. (2001). Discrete network location models, In book: Facility Location; Applications and theory. Editors: Z. Drezner and H. Hamacher, Springer, Heidelberg, 80-118.
[2] Warszawski, A., Peer, S. (1973). Optimizing the location of facilities on a building site. Journal of the Operational Research Society, 24, 35–44.
[3] Syam S.S. (2002). A model and methodologies for the location problem with logistical components. Computers and Operations Research, 29, 1173–1193.
[4] Church, R., ReVelle, C. (1974). The maximal covering location problem. Papers of the Regional Science Association, 32, 101–18.
[5] Schilling, D., Jayaraman, V., Barkhi, R. (1993). A review of covering problems in facility location. Location Science, 1, 25-55.
[6] Galvao, R.D., ReVelle. C. (1996). A Lagrangean heuristic for the maximal covering location problem. European Journal of Operational Research, 88, 114–23.
[7] Gendreau, M., Laporte, G., Semet, F. (2006). The maximal expected coverage relocation problem for emergency vehicles. Journal of Operational Research Society, 57, 22–28.
[8] ReVelle, C. (2008). Solving the maximal covering location problem with heuristic Concentration. Computers & Operations Research, 35, 427 – 435.
[9] Karasakal, O. (2004). A maximal covering location model in the presence of partial coverage. Computers & Operations Research, 31, 1515–1526.
[10] Mestre, J. (2008). Lagrangian relaxation and partial cover. In: Proceedings of the 25th Annual Symposium on Theoretical Aspects of Computer Science, 539–550.
[11] Melo, M.T., Nickel, S., Saldanha-da-Gama, F. (2009). Facility location and supply chain management a review. European Journal of Operational Research, 196, 401-412.
[12] Pereira, M.A., Coelho, L.C., Lorena, L.A.N., De Souza, L.C. (2015). A hybrid method for the probabilistic maximal covering location-allocation problem. Computers & Operations Research, 57, 51-59.
[13] Seifbarghy, M., Soleimani, M., Pishva, D. (2016). Multiple commodity supply chain with maximal covering approach in a three layer structure. International Journal of Mathematical Modeling and Numerical Optimization, 7 (2), 138-161.
[14] Li, X., Ramshani, M., Huang, Y. (2018). Cooperative maximal covering models for humanitarian relief chain management. Computers & Industrial Engineering, 119, 301-308.
[15] Eidy, A., Torabi, H. (2019). A maximal covering problem in supply chain considering variable radius and gradual coverage with the choice of transportation mode. Arabian Journal for science and Engineering, 44, 7219-7233.
[16] Vatsa, A.K., Jayaswal, S. (2021). Capacitated multi-period maximal covering location problem with server uncertainty. European Journal of Operational Research, 289 (3), 1107-1126.
[17] Karasakal, E., Silav, A. (2016). A multi-objective genetic algorithm for a bi-objective facility location problem with partial coverage. TOP, 24, 206-232.
[18] Cordeau, J-F., Furini, F., Ljubic, I. (2019). Benders decomposition for very large scale partial set covering and maximal covering location problems. European Journal of Operational Research, 275(3), 882-896.
[19] El-Hosseini, M., ZainEldin, H., Arafat, H., Badawy, M. (2021). A fire detection model based on power-aware scheduling for IoT-sensors in smart cities with partial coverage. Journal of Ambient Intelligence and Humanized Computing, 12, 2629–2648.
[20] Deb, K., Agrawal, S., Pratap, A., Meyarivan, T. (2000). A fast elitist non-dominated sorting genetic algorithm for multi- Objective optimization: NSGA-II. In: Proceedings of the parallel problem solving from nature VI (PPSN-VI) conference, 849-858.
[21] Al jadaan, O., Rao, C.R., Rajamani, L. (2008). Non-dominated ranked genetic algorithm for solving multi-objective optimization problems: NRGA. Journal of Theoretical and Applied Information Technology, 60-67.
[22] Coello Coello, C., Lamont, G.B., Van Veldhuizen, D.A. (2007). Evolutionary algorithms for solving multi-objective problem. 2nd end, Springer, Berlin.
[23] Sharaf, A.M., Elgammal, A. (2009). A multi objective multistage particle swarm optimization MOPSO search scheme for power quality and loss reduction on radial distribution system. In Proceedings of the International Conference on Renewable Energies and Power Quality (ICREPQ’09).
[24] Zitzler, E., Thiele, L. (1998). Multiobjective optimization using evolutionary algorithms- a comparative case study. Fifth International Conference on Parallel Problem Solving from Nature (PPSN-V), Berlin, Germany, 292-301.