-بایگان، بهروز.، مهرابیان، احمد.، یوسفی نژاد عطاری، مهدی.، دوستی دیلمی، محمد جعفر.،(1403). مدل سازی مساله مکان یابی- مسیریابی لجستیک امدادی با در نظر گرفتن انواع افراد تحت شرایط عدم قطعیت. فصلنامه مدیریت زنجیره تامین، دوره26، شماره82، 66-55.
-بیگی، سکینه.، و حسین زاده، ااهام.،(1398). یک مدلسازی ریاضی مکانیابی- مسیریابی در شرایط بحرانی با در نظر گرفن امنیت مسیر. آینده پژوهی دفاهی، دوره4، شماره13، 110-89.
-جعفری، عزیزالله. و صادقی سروستانی، آیلین.،(1393). مدلسازی مساله مکانیابی- مسیریابی باز با تحویل چند بخشی و حل آن با استفاده از الگوریتم انجماد تدریجی. پژوهشهای مهندسی صنایع در سیستمهای تولید، دوره1، شماره3، 61-47.
-خورسی دامغانی، ملیحه.، چهارسوقی، سید کمال.، حسین زاده کاشان، علی.، و بزرگی امیری، علی.،(1400). ارائه مدل بهینهسازی استوار پویا برای مساله مسیریابی-زمانبندی در لجستیک بشردوستانه و حل آن با استفاده از الگوریتم فراابتکاری گروهبندی (مطالعه موردی: زلزله تهران). فصلنامه مهندسی حمل و نقل، دوره12،شماره4، 853-833.
-عطائی، اسفندیار.، صادقیان، رامین. و حامدی، مریم.،(1399). ارایه یک مدل چندهدفه یکپارچه برای مکانیابی- مسیریابی و موجودی تسهیلات امدادی با در نظر گرفتن چند مد حمل و نقل و تور پوششی. پژوهشنامه حمل و نقل، دوره2، شماره63،66-49.
-گل محمدی، سجاد.، و ماهوتچی، مسعود.، (1396). توسعه یک مدل تصادفی برای ایجاد یک شبکه امدادرسانی پس از بلایای طبیعی (مطالعه موردی: زلزله احتمالی در شهر تهران). نشریه تخصصی مهندسی صنایع، دوره51، شماره11، 433-417.
-Bozorgi-Amiri, A., & Khorsi, M. (2016). A dynamic multi-objective location–routing model for relief logistic planning under uncertainty on demand, travel time, and cost parameters. The International Journal of Advanced Manufacturing Technology, Vol. 85, 1633–1648.
-Cheng, C., Qi, M., Zhang, Y., and Rousseau, L. (2018). A two-stage robust approach for the reliable logistics network design problem. Transportation Research Part B: Methodological, Vol. 111, 185–202.
-Chang, K. H., Chiang, Y. C., and Chang, T. Y. (2024). Simultaneous location and vehicle fleet sizing of relief goods distribution centers and vehicle routing for post-disaster logistics. Computers & Operations Research, Vol. 161, Article 106404.
-Diabat, A., Jabbarzadeh, A. and Khosrojerdi, A., (2019). A perishable product supply chain network design problem with reliability and disruption considerations. International Journal of Production Economics, Vol. 212, 125-138.
-Davoodi, S.M.R. and Goli, A., (2019).An integrated disaster relief model based on covering tour using hybrid Benders decomposition and variable neighborhood search: Application in the Iranian context. Computers & Industrial Engineering, Vol. 130, 370-380.
-Dror, M., Laporte, G., Trudeau, P., (1994). Vehicle routing with split deliveries. Discrete Appl. Math, Vol.50, 239–254.
-Davoodi, S.M.R. and Goli, A., (2019).An integrated disaster relief model based on covering tour using hybrid Benders decomposition and variable neighborhood search: Application in the Iranian context. Computers & Industrial Engineering, Vol. 130, 370-380.
-Deb, K., Pratap, A., Agarwal, S. and Meyarivan, T., (2002). A Fast and Elitist Multiobjective Genetic Algorithm: NSGAII. IEEE Transactions of Evolutionary Computation, Vol. 6, No. 2,
182-197.
-Gunawan, A., Widjaja A.T., Vansteenwegen P., and Yu V.F., (2022). Two-phase Matheuristic for the vehicle routing problem with reverse cross-docking. Annals of Mathematics and Artificial Intelligence, Vol.9, 915-945.
-Hansen, P.H., Hegedahl, B., Hjortkjaer, S., Obel, B., (1994). A heuristic solution to the warehouse location–routing problem. Eur. J. Oper. Res, Vol.76, 111–127.
-Hildebrandt, F.D., Thomas, B.W., Ulmer, M.W., (2023). Opportunities for reinforcement learning in stochastic dynamic vehicle routing. Computers & Operations Research, Vol,150, 60-71.
-
Habibi, M., Paydar, M.M. and Asadi Gangraj, E., (2018). Designing a bi-objective multi-echelon robust blood supply chain in a disaster. Applied Mathematical Modelling, Vol. 55, 583-599.
-Hosseini-Motlagh, S.M., Ghatreh-Samani, M.R. and Cheraghi, S., (2020). Robust and stable flexible blood supply chain network design under motivational initiatives. Socio-Economic Planning Sciences, Vol. 70, Article 100725.
-Imani, A., Karimi, H., & Deiranlou, M. (2024). The bi-objective multi-depot split delivery location routing problems under uncertain conditions. International Journal of Systems Science: Operations & Logistics, Vol. 11, Article 2322512.
-Maghfiroh, M. and Hanaoka, S., (2020).
Multi-modal relief distribution model for disaster response operations. Progress in Disaster Science, Vol.6, 1-12.
-Mavrotas, G., (2009). Effective implementation of the constraint method in multi-objective mathematical programming problems”, Applied mathematics and computation, Vol. 213, 455465.
-Mirjalili, S., Saremi, S., Mirjalili, S. M., & Coelho, L. D. S. (2016). Multi-objective grey wolf optimizer: a novel algorithm for multi-criterion optimization. Expert Systems with Applications, Vol.47, 106-119.
-Noham R., and Tzur M., (2018). Designing humanitarian supply chains by incorporating actual post-disaster decisions. European Journal of Operational Research, Vol. 265, No. 3,1064-1077.
-
Okan, Ö. and Ekici, A., (2018). Managing platelet supply through improved routing of blood collection vehicles. Computers & Operations Research, Vol. 98, 113-126.
-Perl, J., Daskin, M.S., (1985). A warehouse location–routing problem. Transp. Res. B 19B, 381–396.
-Parayoga, R. and Asih, A.M.S., (2022).Multi-objective Multi-Compartment Split Delivery Location Routing Problem with Time Windows. International Conference on Industrial Engineering and Engineering Management (IEEM).
doi:10.1109/IEEM55944.2022.9989684
-Ramezanian, R. and Behboodi, Z., (2017). Blood supply chain network design under uncertainties in supply and demand considering social aspects. Transportation Research Part E: Logistics and Transportation Review, Vol. 104, 69-82.
-Sun, C., Cheng, C., Wang, C., and Hsiao, P. (2020). Dynamic floating stations model for emergency medical services with a consideration of traffic data. ISPRS International Journal of Geo-Information, Vol,9, No,6, 336-345.
-Eydi, A., and Dehnavi, Z. (2025).Multi-objective location-routing problem with decision-making about buying or renting vehicle. Journal of Industrial and Management Optimization, Vol. 21, 6044–6083.
-Tavana, M., Abtahi, A.R, Di Caprio, D., Hashemi, R. and Yousefi-Zenouz, R., (2018).An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations.
Socio-Economic Planning Sciences, Vol. 64,21-37.
-Tzeng, G.H., Cheng, H.J., Huang, T.D., (2007). Multi-objective optimal planning for designing relief delivery systems. Transportation Research Part E: Logistics and Transportation Review, Elsevier, Vol. 43(6), 673-686.
-Wang, Q., and Nie, X. (2022). A stochastic programming model for emergency supply planning considering transportation network mitigation and traffic congestion.
Socio-Economic Planning Sciences, Vol. 79,11-19.
-Wang, Y., Dong, Z. S., and Hu, S. (2021).A stochastic prepositioning model for distribution of disaster supplies considering lateral transshipment. Socio-Economic Planning Sciences, Vol. 74, 9-30.
-Zhang, L., Yuan, N., Wang, J., Jizhao, L., (2025). Research on location-inventory-routing optimization of emergency logistics based on multiple reliability under uncertainty. Vol. 200,8-26.