Presenting an Integrated Multi-Objective Model for Location-Routing and Inventory of Relief Facilities, Considering Several Modes of Transport and Covering Tour

Document Type : Original Article

Authors

Department of Industrial Engineering, Payame Noor University, Tehran, Iran.

Abstract

One of the most important parts when any accident occurs is the issue of control and management before and after the disaster, and if this issue is not taken into account, another secondary catastrophe will occur within the main catastrophe. Therefore, in this study, a random integrated model is proposed. In which two categories of decisions are considered; decisions of the first stage of determining and controlling the inventory of distribution centers and location of distribution centers for pre-disaster and decisions of the second stage for post-disaster, including reviewing the flow of injured, Corpses, homeless and relief items in the network and the allocation of vehicles for this flow. Objectives of this paper include (1) maximizing the probability of successful passage of routes by increasing the reliability of routes, (2) minimizing relief costs pre-disaster and post-disaster, by considering the time window, (3) Minimize maximum uncovered demand for relief goods, for all centers in possible scenarios and situations. Considering the scenario uncertainty situation along with the uncertainty of the route and demand, multi-commodity, several modes of transportation and covering tour are among the innovations of this research. To validate the proposed model in small and medium dimensions, Epsilon restriction method in Gams software environment and for case study (Region 1 of Tehran) in large dimensions has been solved using Invasive Weed Optimization algorithm. The results of the analysis indicate that the Invasive Weed Optimization algorithm will be able to solve the model with the least error compared to the exact solution and less time. Also, as the capacity of distribution centers increases, the cost decreases and as demand increases, the number of established distribution centers increases, and as the coverage radius increases, the length of the tour decreases but the number of unoccupied accident hotspots increases and relief costs, including transportation costs, increase.

Keywords


- حسینی­نژاد، س.ف.، ماکویی، ا. و توکلی­مقدم، ر.، (1397)، "مدل­سازی مکانیابی هاب زنجیره امداد­رسانی در مدیریت بحران بر مبنای نیاز مصدومین تصادفات جاده­ای" پژوهشنامه حمل و نقل، دوره پانزدهم، شمار سوم، ص. 321-335.
 
-Burak, Kõ., Yetis- Kara, B., Saldanha-da-Gama, F. and Correia, I., (2019), “Modeling the shelter site location problem using chance constraints: A case study for Istanbul”, European Journal of Operational Research, Vol.270, No.1, pp. 132-145.
 
- 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, pp.370-380.
 
-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
pp. 125-138.
-Golabi, M., Shavarani, S.M. & Izbirak, G., (2017), “An edge-based stochastic facility location problem in UAV-supported humanitarian relief logistics: a case, study of Tehran earthquake,Natural Hazards”, Vol.87, No.3, pp. 1545–1565.
 
-Habibi, M., Paydar, M.M. and AsadiGangraj, E., (2018), “Designing a bi-objective multi-echelon robust blood supply chain in a disaster”, Applied Mathematical Modelling, Vol. 55, pp. 583-599.
 
-Hasani, A. and Mokhtari, H., (2018), “Redesign strategies of a comprehensive robust relief network for disaster management”, Socio-Economic Planning ciences,  vol.64, pp. 92-102..
 
-Jafarkhan, F. and Yaghoubi, S., (2019), “An efficient solution method for the flexible and robust inventory-routing of red blood cells”, Computers & Industrial Engineering, vol.117, pp.191-206.
 
-Karimkashi, S. & Kishk, A. A., (2010), “Invasive weed optimization and its features in electromagnetics”, IEEE transactions on antennas and propagation, vol.58, No.4, pp.1269-1278.
 
-Karaoğlan, I., Erdoğan, G. and Koç, Ç., (2018), “The Multi-Vehicle Probabilistic Covering Tour Problem”, European Journal of Operational Research, Vol.271, No.1,  pp.278-287.
 
-Mavrotas, G., (2009), “Effective implementation of the ε-constraint method in multi-objective mathematical programming problems”, Applied mathematics and computation, Vol. 213,  pp.455-465.
 
-Mehrabian, A. R. and Lucas, C., (2006), “A novel numerical optimization algorithm inspired from weed colonization”, Ecological informatics , Vol.1, No.4, pp. 355-366.
 
-Moreno, A.,  Alem, D.,   Ferreira, D. and  Clark, a., (2018), “A mathematical model for efficient emergency transportation in a disaster situation”, American Journal of Emergency Medicine, Vol.36, No.9,               pp. 1585-1590.
-Nathalie, C. and Victor, C., (2019), “Including deprivation costs in facility location models for humanitarian relief logistics”, Socio-Economic Planning Sciences, Vol.65, pp. 89–100.
 
-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, pp.1064-1077.
 
-Ni, W., Shu, J. and Song, M., (2018), “Location and Emergency Inventory Pre-Positioning for Disaster Response Operations: Min-Max Robust Model and a Case Study of Yushu Earthquake”, Production and Operation Management; Vol.27, No.1, pp.160–183.
 
-Nikoo, N., Babaei, M. and Shariat-Mohaymany, A., (2018), “Emergency Transportation Network Design Problem: Identification and Evaluation of Disaster Response Routes”, International Journal of Disaster RiskReduction, vol.27, pp.7-20.
 
-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, pp.21-37.
 
-Taguchi, G., Chowdhury, S. and Wu, Y. (2005), "Taguchi’s quality engineering handbook", Wiley Publishing.
 
-Tavakkoli-Moghaddam,  R. and Raziei, Z. (2016), “A New Bi-Objective Location-Routing-Inventory Problem with Fuzzy Demands”, IFAC, Vol.49, No.12, pp.1116 –1121.
 
 -“The Study on Seismic Microzoning of the Greater Tehran Area in the Islamic Republic of Iran”, (2000). Japan International Cooperation Agency (JICA).
 
-Zokaee, S., Bozorgi-Amiri, A. and Sadjadi, S.J. (2016), “A Robust Optimization Model for Humanitarian Relief Chain Design under Uncertainty”, Applied Mathematical Modelling, Vol.40, No.17–18, pp.7996-8016.