[1] Simchi-Levi, D., Kaminsky, P., Simchi-Levi, E. (2004). Managing the supply chain: the definitive guide for the business professional. https://digital.library.tu.ac.th/tu_dc/frontend/Info/item/dc:272468.
[2] Rand, G. K. (1976). Methodological choices in depot location studies. Journal of the operational research society, 27, 241–249.
[3] Contardo, C., Hemmelmayr, V., & Crainic, T. G. (2012). Lower and upper bounds for the two-echelon capacitated location-routing problem. Computers & operations research, 39(12), 3185–3199.
[4] Prodhon, C., & Prins, C. (2014). A survey of recent research on location-routing problems. European journal of operational research, 238(1), 1–17.
[5] Mohamed, I. B., Klibi, W., Sadykov, R., Sen, H., & Vanderbeck, F. (2023). The two-echelon stochastic multi-period capacitated location-routing problem. European journal of operational research, 306(2), 645–667.
[6] Toro, E. M., Franco, J. F., Echeverri, M. G., & Guimarães, F. G. (2017). A multi-objective model for the green capacitated location-routing problem considering environmental impact. Computers & industrial engineering, 110, 114–125.
[7] Nagy, G., & Salhi, S. (2007). Location-routing: Issues, models and methods. European journal of operational research, 177(2), 649–672.
[8] Lopes, R. B., Ferreira, C., Santos, B. S., & Barreto, S. (2013). A taxonomical analysis, current methods and objectives on location-routing problems. International transactions in operational research, 20(6), 795–822.
[9] Ponboon, S., Qureshi, A. G., & Taniguchi, E. (2016). Branch-and-price algorithm for the location-routing problem with time windows. Transportation research part E: logistics and transportation review, 86, 1–19.
[10] Drexl, M., & Schneider, M. (2015). A survey of variants and extensions of the location-routing problem. European journal of operational research, 241(2), 283–308.
[11] Bent, R. W., & Van Hentenryck, P. (2004). Scenario-based planning for partially dynamic vehicle routing with stochastic customers. Operations research, 52(6), 977–987.
[12] Prins, C., Prodhon, C., & Calvo, R. W. (2006). Solving the capacitated location-routing problem by a GRASP complemented by a learning process and a path relinking. 4or, 4, 221–238.
[13] Barreto, S., Ferreira, C., Paixao, J., & Santos, B. S. (2007). Using clustering analysis in a capacitated location-routing problem. European journal of operational research, 179(3), 968–977.
[14] Balcik, B., & Beamon, B. M. (2008). Facility location in humanitarian relief. International journal of logistics, 11(2), 101–121.
[15] Vincent, F. Y., Lin, S. W., Lee, W., & Ting, C.-J. (2010). A simulated annealing heuristic for the capacitated location routing problem. Computers & industrial engineering, 58(2), 288–299.
[16] Duhamel, C., Lacomme, P., Prins, C., & Prodhon, C. (2010). A GRASP×ELS approach for the capacitated location-routing problem. Computers & operations research, 37(11), 1912–1923.
[17] Li, X., & Ouyang, Y. (2010). A continuum approximation approach to reliable facility location design under correlated probabilistic disruptions. Transportation research part B: methodological, 44(4), 535–548.
[18] Peng, P., Snyder, L. V, Lim, A., & Liu, Z. (2011). Reliable logistics networks design with facility disruptions. Transportation research part B: methodological, 45(8), 1190–1211.
[19] Bozorgi-Amiri, A., Jabalameli, M. S., & Mirzapour Al-e-Hashem, S. M. J. (2013). A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty. OR spectrum, 35, 905–933.
[20] Cardona-Valdés, Y., Álvarez, A., & Ozdemir, D. (2011). A bi-objective supply chain design problem with uncertainty. Transportation research part C: emerging technologies, 19(5), 821–832.
[21] Jokar, A., & Sahraeian, R. (2012). A heuristic based approach to solve a capacitated location-routing problem. Journal of managment & sustainability, 2, 219. https://heinonline.org/HOL/LandingPage?handle=hein.journals/jms2&div=44&id=&page=
[22] Cui, T., Ouyang, Y., & Shen, Z. J. M. (2010). Reliable facility location design under the risk of disruptions. Operations research, 58(4-part-1), 998–1011.
[23] Escobar, J. W., Linfati, R., & Toth, P. (2013). A two-phase hybrid heuristic algorithm for the capacitated location-routing problem. Computers & operations research, 40(1), 70–79.
[24] Ghaffari-Nasab, N., Jabalameli, M. S., Aryanezhad, M. B., & Makui, A. (2013). Modeling and solving the bi-objective capacitated location-routing problem with probabilistic travel times. The international journal of advanced manufacturing technology, 67, 2007–2019.
[25] Golozari, F., Jafari, A., & Amiri, M. (2013). Application of a hybrid simulated annealing-mutation operator to solve fuzzy capacitated location-routing problem. The international journal of advanced manufacturing technology, 67, 1791–1807.
[26] Zarandi, M. H. F., Hemmati, A., Davari, S., & Turksen, I. B. (2013). Capacitated location-routing problem with time windows under uncertainty. Knowledge-based systems, 37, 480–489.
[27] Mehrjerdi, Y. Z., & Nadizadeh, A. (2013). Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands. European journal of operational research, 229(1), 75–84.
[28] Ahmadi-Javid, A., & Seddighi, A. H. (2013). A location-routing problem with disruption risk. Transportation research part E: logistics and transportation review, 53, 63–82.
[29] Gounaris, C. E., Wiesemann, W., & Floudas, C. A. (2013). The robust capacitated vehicle routing problem under demand uncertainty. Operations research, 61(3), 677–693.
[30] Azad, N., Davoudpour, H., Saharidis, G. K. D., & Shiripour, M. (2014). A new model to mitigating random disruption risks of facility and transportation in supply chain network design. The international journal of advanced manufacturing technology, 70, 1757–1774.
[31] Rennemo, S. J., Rø, K. F., Hvattum, L. M., & Tirado, G. (2014). A three-stage stochastic facility routing model for disaster response planning. Transportation research part E: logistics and transportation review, 62, 116–135.
[32] An, Y., Zeng, B., Zhang, Y., & Zhao, L. (2014). Reliable p-median facility location problem: two-stage robust models and algorithms. Transportation research part B: methodological, 64, 54–72.
[33] Karaoglan, I., & Altiparmak, F. (2015). A memetic algorithm for the capacitated location-routing problem with mixed backhauls. Computers & operations research, 55, 200–216.
[34] Peng, Z., Manier, H., & Manier, M. A. (2017). Particle swarm optimization for capacitated location-routing problem. IFAC-papersonline, 50(1), 14668–14673.
[35] Huang, S. H. (2015). Solving the multi-compartment capacitated location routing problem with pickup--delivery routes and stochastic demands. Computers & industrial engineering, 87, 104–113.
[36] Zhang, Y., Qi, M., Lin, W. H., & Miao, L. (2015). A metaheuristic approach to the reliable location routing problem under disruptions. Transportation research part E: logistics and transportation review, 83, 90–110.
[37] Lopes, R. B., Ferreira, C., & Santos, B. S. (2016). A simple and effective evolutionary algorithm for the capacitated location--routing problem. Computers & operations research, 70, 155–162.
[38] Tang, L., Zhu, C., Lin, Z., Shi, J., & Zhang, W. (2016). Reliable facility location problem with facility protection. PloS one, 11(9), e0161532. https://doi.org/10.1371/journal.pone.0161532
[39] de Queiroz, T. A., Oliveira, J. F., Carravilla, M. A., & Miyazawa, F. K. (2016). Demand uncertainty for the location-routing problem with two-dimensional loading constraints [presentation]. Computational management science: state of the art 2014 (pp. 47–53).
[40] Quintero-Araujo, C. L., Caballero-Villalobos, J. P., Juan, A. A., & Montoya-Torres, J. R. (2017). A biased-randomized metaheuristic for the capacitated location routing problem. International transactions in operational research, 24(5), 1079–1098.
[41] Sadegheih, A. (2017). A hybrid heuristic algorithm to solve capacitated location-routing problem with fuzzy demands. International journal of industrial mathematics, 9(1), 1–20.
[42] Chang, K., Zhou, H., Chen, G., & Chen, H. (2017). Multiobjective location routing problem considering uncertain data after disasters. Discrete dynamics in nature and society, 2017. https://doi.org/10.1155/2017/1703608
[43] Farham, M. S., Süral, H., & Iyigun, C. (2018). A column generation approach for the location-routing problem with time windows. Computers & operations research, 90, 249–263.
[44] Madani, S. R., Nookabadi, A. S., & Hejazi, S. R. (2018). A bi-objective, reliable single allocation p-hub maximal covering location problem: Mathematical formulation and solution approach. Journal of air transport management, 68, 118–136.
[45] Zhang, B., Li, H., Li, S., & Peng, J. (2018). Sustainable multi-depot emergency facilities location-routing problem with uncertain information. Applied mathematics and computation, 333, 506–520.
[46] Ghaderi, A. (2018). A robust optimization model for the single-depot capacitated location-routing problem. International journal of computer and information engineering, 12(7), 504–508.
[47] Zhao, Q., Wang, W., & De Souza, R. (2018). A heterogeneous fleet two-echelon capacitated location-routing model for joint delivery arising in city logistics. International journal of production research, 56(15), 5062–5080.
[48] Hosseini, M. B., Dehghanian, F., & Salari, M. (2019). Selective capacitated location-routing problem with incentive-dependent returns in designing used products collection network. European journal of operational research, 272(2), 655–673.
[49] Pekel, E., & Kara, S. S. (2019). Solving fuzzy capacitated location routing problem using hybrid variable neighborhood search and evolutionary local search. Applied soft computing, 83, 105665. https://doi.org/10.1016/j.asoc.2019.105665
[50] Tirkolaee, E. B., Mahmoodkhani, J., Bourani, M. R., & Tavakkoli-Moghaddam, R. (2019). A self-learning particle swarm optimization for robust multi-echelon capacitated location--allocation--inventory problem. Journal of advanced manufacturing systems, 18(04), 677–694.
[51] Oudouar, F., Lazaar, M., & El Miloud, Z. (2020). A novel approach based on heuristics and a neural network to solve a capacitated location routing problem. Simulation modelling practice and theory, 100, 102064. https://doi.org/10.1016/j.simpat.2019.102064.
[52] Zhang, H., Liu, F., Ma, L., & Zhang, Z. (2020). A hybrid heuristic based on a particle swarm algorithm to solve the capacitated location-routing problem with fuzzy demands. IEEE access, 8, 153671–153691.
[53] Wang, M., Bell, M. G. H., & Miao, L. (2020). A branch-and-price algorithm for a green two-echelon capacitated location routing problem. https://ses.library.usyd.edu.au/handle/2123/21882
[54] Akpunar, Ö. S., & Akpinar, S. (2021). A hybrid adaptive large neighbourhood search algorithm for the capacitated location routing problem. Expert systems with applications, 168, 114304. https://doi.org/10.1016/j.eswa.2020.114304.
[55] Negrotto, D., & Loiseau, I. (2021). A branch & cut algorithm for the prize-collecting capacitated location routing problem. Top, 29(1), 34–57.
[56] Vincent, F. Y., Normasari, N. M. E., & Chen, W. H. (2021). Location-routing problem with time-dependent demands. Computers & industrial engineering, 151, 106936. https://doi.org/10.1016/j.cie.2020.106936.
[57] Ziaei, Z., & Jabbarzadeh, A. (2021). A multi-objective robust optimization approach for green location-routing planning of multi-modal transportation systems under uncertainty. Journal of cleaner production, 291, 125293. https://doi.org/10.1016/j.jclepro.2020.125293.
[58] Turkensteen, M. (2017). The accuracy of carbon emission and fuel consumption computations in green vehicle routing. European journal of operational research, 262(2), 647–659.
[59] Chen, D. S., Batson, R. G., & Dang, Y. (2011). Applied integer programming: modeling and solution. John Wiley & Sons.
[60] Mulvey, J. M., & Ruszczyński, A. (1995). A new scenario decomposition method for large-scale stochastic optimization. Operations research, 43(3), 477–490.
[61] Pan, F., & Nagi, R. (2010). Robust supply chain design under uncertain demand in agile manufacturing. Computers & operations research, 37(4), 668–683.
[62] Yu, C. S., & Li, H. L. (2000). A robust optimization model for stochastic logistic problems. International journal of production economics, 64(1–3), 385–397.
[63] Haimes, Y. (1971). On a bicriterion formulation of the problems of integrated system identification and system optimization. IEEE transactions on systems, man, and cybernetics, (3), 296–297.
[64] Fan, J., & Wang, G. (2018). Joint optimization of dynamic lot and warehouse sizing problems. European journal of operational research, 267(3), 849–854.
[65] Cao, E., Lai, M., & Yang, H. (2014). Open vehicle routing problem with demand uncertainty and its robust strategies. Expert systems with applications, 41(7), 3569–3575.
[66] Ruiz, E., Soto-Mendoza, V., Barbosa, A. E. R., & Reyes, R. (2019). Solving the open vehicle routing problem with capacity and distance constraints with a biased random key genetic algorithm. Computers & industrial engineering, 133, 207–219.
[67] Shiripour, S., Mahdavi-Amiri, N., & Mahdavi, I. (2017). A transportation network model with intelligent probabilistic travel times and two hybrid algorithms. Transportation letters, 9(2), 90–122.
[68] Fazayeli, S., Eydi, A., & Kamalabadi, I. N. (2018). Location-routing problem in multimodal transportation network with time windows and fuzzy demands: Presenting a two-part genetic algorithm. Computers & industrial engineering, 119, 233–246.
[69] Cardoso, S. R., Barbosa-Póvoa, A. P. F. D., & Relvas, S. (2013). Design and planning of supply chains with integration of reverse logistics activities under demand uncertainty. European journal of operational research, 226(3), 436–451.
[70] Université Paris-Nord. (2010). Classical instances for LRP. http://prodhonc.free.fr/Instances/instances_us.htm
)