[1] Díaz-Madroñero, M., Mula, J., Jiménez, M., & Peidro, D. (2017). A rolling horizon approach for material requirement planning under fuzzy lead times. International journal of production research, 55(8), 2197–2211. DOI:10.1080/00207543.2016.1223382
[2] Armentano, V. A., Shiguemoto, A. L., & Løkketangen, A. (2011). Tabu search with path relinking for an integrated productiondistribution problem. Computers and operations research, 38(8), 1199–1209. DOI:10.1016/j.cor.2010.10.026
[3] Adulyasak, Y., Cordeau, J. F., & Jans, R. (2015). The production routing problem: A review of formulations and solution algorithms. Computers and operations research, 55, 141–152. DOI:10.1016/j.cor.2014.01.011
[4] Chandra, P., & Fisher, M. L. (1994). Coordination of production and distribution planning. European journal of operational research, 72(3), 503–517. DOI:10.1016/0377-2217(94)90419-7
[5] Fortes, A., Camargo, R., Muniz, L. R., Lima, F. M. de S., & Cota, F. dos R. (2022). Efficient matheuristics to solve a rich production-routing problem. Computers and industrial engineering, 171, 108369. DOI:10.1016/j.cie.2022.108369
[6] Erkut, E., & Verter, V. (1998). Modeling of transport risk for hazardous materials. Operations research, 46(5), 625–642. DOI:10.1287/opre.46.5.625
[7] Holeczek, N. (2019). Hazardous materials truck transportation problems: A classification and state of the art literature review. Transportation research part d: transport and environment, 69, 305–328. DOI:10.1016/j.trd.2019.02.010
[8] Kané, L., Diakité, M., Kané, S., Bado, H., Konaté, M., & Traoré, K. (2021). A new algorithm for fuzzy transportation problems with trapezoidal fuzzy numbers under fuzzy circumstances. Journal of fuzzy extension and applications, 2(3), 204–225.
[9] Bianco, L., Caramia, M., & Giordani, S. (2009). A bilevel flow model for HAZMAT transportation network design. Transportation research part c: emerging technologies, 17(2), 175–196. DOI:10.1016/j.trc.2008.10.001
[10] Kalelkar, A. S., & Brooks, R. E. (1978). Use of multidimensional utility functions in hazardous shipment decisions. Accident analysis and prevention, 10(3), 251–265. DOI:10.1016/0001-4575(78)90016-7
[11] Pourghade Chobar, A., Sabk ara, M., Moradi Pirbalouti, S., Khadem, M., & Bahrami, S. (2021). A Multi-Objective Location-Routing Problem Model for Multi-Device Relief Logistics under Uncertainty Using Meta-Heuristic Algorithm. Journal of applied research on industrial engineering, 9(3), 354–373.
[12] Fan, L. (2022). A short study of the components and applications of wireless sensor network. Big data and computing visions, 2(2), 101–106.
[13] Erkut, E., Tjandra, S. A., & Verter, V. (2007). Hazardous materials transportation. Handbooks in operations research and management science, 14, 539–621.
[14] Bianco, L., Caramia, M., Giordani, S., & Piccialli, V. (2013). International series in operations research and management science. Springer. Academic Journals.
[15] Bula, G. A., Prodhon, C., Gonzalez, F. A., Afsar, H. M., & Velasco, N. (2017). Variable neighborhood search to solve the vehicle routing problem for hazardous materials transportation. Journal of hazardous materials, 324, 472–480. DOI:10.1016/j.jhazmat.2016.11.015
[16] Bula, G. A., Murat Afsar, H., González, F. A., Prodhon, C., & Velasco, N. (2019). Bi-objective vehicle routing problem for hazardous materials transportation. Journal of cleaner production, 206, 976–986. DOI:10.1016/j.jclepro.2018.09.228
[17] Du, J., Li, X., Yu, L., Dan, R., & Zhou, J. (2017). Multi-depot vehicle routing problem for hazardous materials transportation: A fuzzy bilevel programming. Information sciences, 399, 201–218.
[18] Men, J., Jiang, P., & Xu, H. (2019). A chance constrained programming approach for HAZMAT capacitated vehicle routing problem in Type-2 fuzzy environment. Journal of cleaner production, 237, 117754. DOI:10.1016/j.jclepro.2019.117754
[19] Zhou, Z., Ha, M., Hu, H., & Ma, H. (2021). Half open multi-depot heterogeneous vehicle routing problem for hazardous materials transportation. Sustainability (switzerland), 13(3), 1–17. DOI:10.3390/su13031262
[20] Fontaine, P., & Minner, S. (2018). Benders decomposition for the HAZMAT Transport Network Design Problem. European journal of operational research, 267(3), 996–1002. DOI:10.1016/j.ejor.2017.12.042
[21] Zhang, L., Feng, X., Chen, D., Zhu, N., & Liu, Y. (2019). Designing a hazardous materials transportation network by a bi-level programming based on toll policies. Physica a: statistical mechanics and its applications, 534, 122324. DOI:10.1016/j.physa.2019.122324
[22] Fontaine, P., Crainic, T. G., Gendreau, M., & Minner, S. (2020). Population-based risk equilibration for the multimode HAZMAT transport network design problem. European journal of operational research, 284(1), 188–200. DOI:10.1016/j.ejor.2019.12.028
[23] Mohabbati-Kalejahi, N., & Vinel, A. (2021). Robust hazardous materials closed-loop supply chain network design with emergency response teams location. Transportation research record, 2675(6), 306–329. DOI:10.1177/0361198121992071
[24] 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. DOI:10.1016/j.jclepro.2020.125293
[25] Tasouji Hassanpour, S., Ke, G. Y., & Tulett, D. M. (2021). A time-dependent location-routing problem of hazardous material transportation with edge unavailability and time window. Journal of cleaner production, 322, 128951. DOI:10.1016/j.jclepro.2021.128951
[26] Bolhasani, P., Fallah, M., Tavakkoli-Moghaddam, R., & Alam Tabriz, A. (2021). Presenting a multi-objective mathematical model of a location-routing-inventory problem for hazardous materials considering the concept elastic demand and queuing system. Journal of decisions and operations research, 6(2), 210–241. (In Persian). https://www.journal-dmor.ir/article_136500_495740a95cc285e0d82b225078bbe378.pdf
[27] Rahbari, M., Arshadi Khamseh, A., Sadati-Keneti, Y., & Jafari, M. J. (2022). A risk-based green location-inventory-routing problem for hazardous materials: NSGA II, MOSA, and multi-objective black widow optimization. Environment, development and sustainability, 24(2), 2804–2840. DOI:10.1007/s10668-021-01555-1
[28] Fang, J. (2022). Smart phone based monitoring of agricultural activities. Computational algorithms and numerical dimensions, 1(4), 159–163.
[29] Salamatbakhsh, A., Tavakkoli-Moghaddam, R., & Pahlevani, A. (2021). Solving a vehicle routing problem under uncertainty by a differential evolution algorithm. Inovation management and operational strategies, 1(4), 310–319. (In Persian). https://doi.org/10.22105/imos.2021.272652.1034
[30] Chen, Z. L. (2010). Integrated production and outbound distribution scheduling: Review and extensions. Operations research, 58(1), 130–148. DOI:10.1287/opre.1080.0688
[31] Low, C., Chang, C. M., Li, R. K., & Huang, C. L. (2014). Coordination of production scheduling and delivery problems with heterogeneous fleet. International journal of production economics, 153, 139–148. DOI:10.1016/j.ijpe.2014.02.014
[32] Li, Y., Chu, F., Chu, C., & Zhu, Z. (2019). An efficient three-level heuristic for the large-scaled multi-product production routing problem with outsourcing. European journal of operational research, 272(3), 914–927. DOI:10.1016/j.ejor.2018.07.018
[33] Hemmati Golsefidi, A., & Akbari Jokar, M. R. (2020). A robust optimization approach for the production-inventory-routing problem with simultaneous pickup and delivery. Computers and industrial engineering, 143, 106388. DOI:10.1016/j.cie.2020.106388
[34] Emamian, Y., Kamalabadi, I. N., & Eydi, A. (2021). Developing and solving an integrated model for production routing in sustainable closed-loop supply chain. Journal of cleaner production, 302, 126997. DOI:10.1016/j.jclepro.2021.126997
[35] Schenekemberg, C. M., Scarpin, C. T., Pecora Jr, J. E., Guimarães, T. A., & Coelho, L. C. (2021). The two-echelon production-routing problem. European journal of operational research, 288(2), 436–449.
[36] Chen, H. K., Hsueh, C. F., & Chang, M. S. (2009). Production scheduling and vehicle routing with time windows for perishable food products. Computers and operations research, 36(7), 2311–2319. DOI:10.1016/j.cor.2008.09.010
[37] Amorim, P., Belo-Filho, M. A. F., Toledo, F. M. B., Almeder, C., & Almada-Lobo, B. (2013). Lot sizing versus batching in the production and distribution planning of perishable goods. International journal of production economics, 146(1), 208–218. DOI:10.1016/j.ijpe.2013.07.001
[38] Lei, L., Liu, S., Ruszczynski, A., & Park, S. (2006). On the integrated production, inventory, and distribution routing problem. IIE transactions (institute of industrial engineers), 38(11), 955–970. DOI:10.1080/07408170600862688
[39] Ganji, M., Kazemipoor, H., Hadji Molana, S. M., & Sajadi, S. M. (2020). A green multi-objective integrated scheduling of production and distribution with heterogeneous fleet vehicle routing and time windows. Journal of cleaner production, 259, 120824. DOI:10.1016/j.jclepro.2020.120824
[40] Li, Y., Chu, F., Côté, J. F., Coelho, L. C., & Chu, C. (2020). The multi-plant perishable food production routing with packaging consideration. International journal of production economics, 221, 107472. DOI:10.1016/j.ijpe.2019.08.007
[41] Bula, G. A., Gonzalez, F. A., Prodhon, C., Afsar, H. M., & Velasco, N. M. (2016). Mixed integer linear programming model for vehicle routing problem for hazardous materials transportation. IFAC-papersonline, 49(12), 538–543. DOI:10.1016/j.ifacol.2016.07.691
[42] Padberg, M. (2000). Approximating separable nonlinear functions via mixed zero-one programs. Operations research letters, 27(1), 1–5. DOI:10.1016/s0167-6377(00)00028-6
[43] Absi, N., Archetti, C., Dauzère-Pérès, S., Feillet, D., & Speranza, M. G. (2018). Comparing sequential and integrated approaches for the production routing problem. European journal of operational research, 269(2), 633–646. DOI:10.1016/j.ejor.2018.01.052
[44] Kazantzi, V., Kazantzis, N., & Gerogiannis, V. C. (2011). Risk informed optimization of a hazardous material multi-periodic transportation model. Journal of loss prevention in the process industries, 24(6), 767–773. DOI:10.1016/j.jlp.2011.05.006
[45] Ronza, A., Vílchez, J. A., & Casal, J. (2007). Using transportation accident databases to investigate ignition and explosion probabilities of flammable spills. Journal of hazardous materials, 146(1–2), 106–123. DOI:10.1016/j.jhazmat.2006.11.057
[46] Reilly, A., Nozick, L., Xu, N., & Jones, D. (2012). Game theory-based identification of facility use restrictions for the movement of hazardous materials under terrorist threat. Transportation research part e: logistics and transportation review, 48(1), 115–131. DOI:10.1016/j.tre.2011.06.002