Azad, N., & Davoudpour, H. (2010). A two echelon location-routing model with considering Value-at-Risk measure. International Journal of Management Science and Engineering Management, 5(3), 235-240. https://doi.org/10.1080/17509653.2010.10671113
Bahrami, F., Safari, H.,Tavakoli-Moghaddam, R., & Modarres Yazdi, M. (2016). On modeling door-to-door parcel delivery services in Iran.
Iranian Journal of Management studies, 9(4), 883-906. https://doi.org/
10.22059/ijms.2017.59944
Bozorgi-Amiri, A., Jabalameli, M.S, & Mirzapour Al-e-Hashem, S.M.J. (2011). A multi-objective robust stochastic programming model for disaster relief logistics under uncertainty. OR Spectrum, 35(4), 905-933. https://doi.org/10.1007/s00291-011-0268-x
Esmaili, M., Amjady, N., & Shayanfar, H.A. (2011). Multi-objective congestion management by modified augmented -constraint method.
Applied Energy, 88(3), 755–766. https://doi.org/
10.1016/j.apenergy.2010.09.014
Farzadnia, F., & Lysgaard, J. (2021). Solving the service-oriented single-route school bus routing problem: Exact and heuristic solutions. EURO Journal on Transportation and Logistics, 10, 100054.
https://doi.org/10.1016/j.ejtl.2021.100054
Guo, R., Guan, W., Zhang, W., Meng, F., & Zheng, Z. (2019). Customized bus routing problem with time window restrictions: Model and case study. Transportmetrica A: Transport Science, 15(2), 1804–1824. https://doi.org/10.1080/23249935.2019.1644566
Leksakul, K., Smutkupt, U., Jintawiwat, R., & Phongmoo, S. (2017). Heuristic approach for solving employee bus routes in a large-scale industrial factory.
Advanced Engineering Informatics, 32, 176–187. https://doi.org/
10.1016/j.aei.2017.02.006
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.
https://doi.org/10.1111/itor.12032
Maranzana, F. E. (1964). On the location of supply points to minimize transport costs. Operational Research Quarterly, 15(3), 261–270. https://doi.org/10.2307/3007214
Mavrotas, G. (2009). Effective implementation of the ε-constraint method in Multi-Objective Mathematical Programming problems.
Applied Mathematics and Computation, 213(2), 455–465. https://doi.org/
10.1016/j.amc.2009.03.037
Miranda, D. M., Camargo, R. S., Conceição, S. V., Porto, M. F., & Nunes, N. T. R. (2021). A metaheuristic for the rural school bus routing problem with bell adjustment. Expert Systems With Applications, 180, 115086. https://doi.org/10.1016/j.eswa.2021.115086
Najafi Moghadam Gilani, V., Hosseinian, S. M., Behbahani, H., & Hamedi, G. H. (2020). Prediction and Pareto-based multi-objective optimization of moisture and fatigue damages of asphalt mixtures modified with Nano hydrated lime. Construction and Building Material, 261, 120509 https://doi.org/10.1016/j.conbuildmat.2020.120509
Najafi Moghadam Gilani, V., Hosseinian, S. M., Ghasedi, M., & Nikookar, M. (2021). Data-driven urban traffic accident analysis and prediction using logit and machine learning-based pattern recognition models. Hindawi, 2021, 9974219.
https://doi.org/10.1155/2021/9974219
Park, J., & Kim, B. I. (2010). The school bus routing problem: A review. European Journal of Operational Research, 202(2), 311–319.
Yüceer, Ü. (2013). An employee transporting problem. Industrial Engineering International, 9(13), 9-31.
https://doi.org/10.1186/2251-712X-9-31