- Aboolian, R., & Berman, O., & Drezner, Z. (2009). The multiple server center location problem.Annals of Operations Research, 167, 337–352.
- Abouee-Mehrizi, H., & Babri, S., & Berman, O., & Shavandi, H. (2011). Optimizing capacity, pricing and location decisions on a congested network with balking. Mathematical Methods of Operations Research, 74(2), 233-255.
- Azzaro-Pantel, C., & Floquet, P., & Pibouleau, L., & Domenech, S. (1997). A fuzzy approach for performance modeling in a batch plant: application to semiconductor manufacturing. IEEE Transactions on Fuzzy Systems, 5(3).
- Berman, O., & Krass, D., & Wang, J. (2006). Locating service facilities to reduce lost demand.IIE Transactions, 38(11), 933 – 946.
- Berman, O., & Larson, R.C., & Chiu, S.S., (1985). Optimal Server Location on A Network Operating as an M/G/1 Queue.Operations Research, 33(4), 746-771.
- Berman, O., & Tong, D., & Krass, D., (2010a). Pricinglocation and capacity planning with elastic demand and congestion. Working paper. University of Toronto.
- Berman, O., Tong, D., & Krass, D. (2010b). Pricing, location and capacity planning with equilibrium driven demand and congestion working paper. University of Toronto.
- Berman, O., (2007). Locating capacitated facilities to maximize captured demand. IIE Transactions, 39(11), 1015-1029.
- Boffey, B., & Galvao, R., & Espejo, L. (2007). A review of congestion models in the location of facilities with immobile servers. European Journal of Operational Research, 178(3), 643–662.
- Brandeau, M. L., & Chiu, S. S. (1990). A unified family of single-server queueing location models. Operations Research, 38(6), 1034-1044.
- Chambari, A.H., & Rahmaty, S.H., & Hajipour, V., & Karimi, A. (2011). A bi-objective model for location-allocation problem within queuing framework. World Academy of Science. Engineering and Technology, 5(6), 138-145.
- Current, J., & Daskin, M., & Schilling, D. (2002). Discrete network location models. facility location: applications and theory. Springer, Heidelberg, 80-118.
- Dong, M., & Wua, C., & Hou, F. (2009). Shortest path based simulated annealing algorithm for dynamic facility layout problem under dynamic business environment. Expert Systems with Applications, 36(8), 11221–11232.
- Farahani, R. Z., SteadieSeifi, M., & Asgari, N. (2010). Multiple criteria facility location problems: A survey. Applied Mathematical Modelling, 34(7), 1689-1709.
- Hakimi, S.L. (1964). Optimum locations of switching centers and the absolute centers andmedians of a graph.Operation Research, 12(3), 450–459.
- Hodgson, M.J., & Berman, O. (1997). A billboard location model, Geographical and Environmental Modeling 1, 25–43.
- Grieco, A. & Nucci, F. & Anglani, A. (2003). Representation of fuzzy time variables in discrete event simulation. Integrated Computer-Aided Engineering, 10(4), 305-318.
- Love, R.L., & Morris, J.G., & Wesolowsky, G.O. (1988). Facility Location: Models and Methods. North-Holland Publishing Company, New York, (Cited by Francis).
- Marianov, V., & Revelle, C. (1995). Siting emergency services in Facility Location: A Survey of Applications and Methods. Springer Series in Operations Research.
- Marianov, V., & Rios, M,. (2000). A probabilistic quality of service constraint for a location model of switches in ATM Communications networks.Annals of Operations Research, 96, 237–243.
- Mehdizadeh, E., & Tavarroth, M.R., & Hajipour, V. (2011). A New hybrid Algorithm to Optimize Stochastic-Fuzzy Capacitated Multi-Facility Location-Allocation Problem. Journal of Industrial Engineering Islamic Azad University of Qazvin, 4(7),71–80.
- Melo, M.T., & Nickel, S., & Saldanha-da-Gama, F. (2009). Facility location and supply chain management – A review. European Journal of Operational Research, 196(2), 401–412.
- Pasandideh, S.H.R., & Niaki, S.D.A. (2010). Genetic application in a facility location problem with random demand within queuing framework.Journal of Intelligent Manufacturing, 23(3), 234-546.
- Pasandideh, S.H.R., & Niaki, STA, & Hajipour, V. (2013). A multi-objective facility location model with batch arrivals: two parameter-tuned meta-heuristic algorithms. Journal of Intelligent Manufacturing, 24(2), 331-348.
- Shanthikumar, J.G., & Yao, D.D., (1987). Optimal Server Allocation in a System of Multi- Server Stations.Management Science, 33(9), 1173-1180.
- Shavandi, H., & Mahlooji, H. (2006). A Fuzzy Queuing Location Model with A Genetic Algorithm Congested Systems. Applied Mathematics and Computation, 181(1), 440 -456.
- Syam, S.S. (2008). A multiple server location–allocation model for service system design.Computers and Operations Research, 35(7), 2248–2265.
- Wang, D., & Fung, R., & Ip, W. (2009). An immune-genetic algorithm for introduction planning of new products. Computers & Industrial Engineering, 56(3), 902–917.
- Wang, Q., & Batta, R., & Rump, C. (2002). Algorithms for a facility location problem with stochastic customer demand and immobile servers. Annals of Operations Research, 111, 17–34.
- Wang, Q., & Batta, R., & Rump, C. (2004). Facility Location Models for Immobile Servers with Stochastic Demand. Naval Research Logistic, 51(1), 137 - 152.
- Zarrinpoor, N., & Seifbarghy, M. (2011). A competitive location model to obtain a specific market share while ranking facilities by shorter travel time. The International Journal of Advanced Manufacturing Technology, 55(5), 807-816.
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