Multi-Objective Optimization Model for Designing a Humanitarian Logistics Network under Service Sharing and Accident Risk Concerns under Uncertainty

Document Type : Research Paper

Authors

Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

10.22070/jqepo.2020.5065.1121

Abstract

A multi-objective mathematical model is proposed to design a humanitarian logistics network under uncertain conditions. Three objective functions are considered to formulate this problem. The first one minimizes the total costs of logistics activities, the second minimizes the maximum overload of local distribution centers, and the third minimizes the maximum accident loss throughout the distribution of relief items. What is more, different simultaneous decisions are determined, including facility location-allocation, service sharing, relief distribution, truck routing, transferring service, and the evacuation of victims. Owing to the fact that the planning of humanitarian logistics problems is encountered with miscellaneous uncertain factors, such as demand, supply, costs, and capacities of facilities, a robust optimization approach is employed to tackle these challenges. Furthermore, a number of numerical instances are provided to illustrate the validity of the proposed mathematical model.

Keywords


Abounacer, R., Rekik, M. and Renaud, J. (2014). An exact solution approach for multi-objective location–transportation problem for disaster response. Computers & Operations Research, 41, pp.83-93.
Ahmadi, M., Seifi, A. and Tootooni, B. (2015). A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district. Transportation Research Part E: Logistics and Transportation Review, 75, pp.145-163.
Balcik, B., Beamon, B.M., Krejci, C.C., Muramatsu, K.M. and Ramirez, M. (2010). Coordination in humanitarian relief chains: Practices, challenges and opportunities. International Journal of Production Economics, 126(1), pp.22-34.
Ben-Tal, A. and Nemirovski, A. (2000). Robust solutions of linear programming problems contaminated with uncertain data. Mathematical programming, 88(3), pp.411-424.
Birjandi, A. and Mousavi, S.M. (2019). Fuzzy resource-constrained project scheduling with multiple routes: A heuristic solution. Automation in Construction, 100, pp.84-102.
Coppola, D.P., 2006. Introduction to international disaster management. Elsevier.
Dufour, É., Laporte, G., Paquette, J. and Rancourt, M.È. (2018). Logistics service network design for humanitarian response in East Africa. Omega, 74, pp.1-14.
Foroozesh, N., Tavakkoli-Moghaddam, R. and Mousavi, S.M. (2018). A novel group decision model based on mean–variance–skewness concepts and interval-valued fuzzy sets for a selection problem of the sustainable warehouse location under uncertainty. Neural Computing and Applications, 30(11), pp.3277-3293.
Gitinavard, H., Mousavi, S.M. and Vahdani, B. (2017). Soft computing based on hierarchical evaluation approach and criteria interdependencies for energy decision-making problems: A case study. Energy, 118, pp.556-577.
Gitinavard, H., Mousavi, S.M. and Vahdani, B. (2017) Soft computing-based new interval-valued hesitant fuzzy multi-criteria group assessment method with last aggregation to industrial decision problems. Soft Computing, 21(12), pp.3247-3265.
Ko, J., Nazarian, E., Nam, Y. and Guo, Y. (2015). Integrated redistricting, location-allocation and service sharing with intra-district service transfer to reduce demand overload and its disparity. Computers, Environment and Urban Systems, 54, pp.132-143.
Maharjan, R. and Hanaoka, S. (2017). Warehouse location determination for humanitarian relief distribution in Nepal. Transportation research procedia, 25, pp.1151-1163.
Mohagheghi, V., Mousavi, S.M. and Vahdani, B. (2015). A new optimization model for project portfolio selection under interval-valued fuzzy environment. Arabian Journal for Science and Engineering, 40(11), pp.3351-3361.
Mohammadi, M., Dehbari, S. and Vahdani, B. (2014). Design of a bi-objective reliable healthcare network with finite capacity queue under service covering uncertainty. Transportation Research Part E: Logistics and Transportation Review, 72, pp.15-41.
Mousavi, S.M., Antuchevičienė, J., Zavadskas, E.K., Vahdani, B. and Hashemi, H. (2019). A new decision model for cross-docking center location in logistics networks under interval-valued intuitionistic fuzzy uncertainty. Transport, 34(1), pp.30-40.
Mousavi, S.M. and Vahdani, B. (2017). A robust approach to multiple vehicle location-routing problems with time windows for optimization of cross-docking under uncertainty. Journal of Intelligent & Fuzzy Systems, 32(1), pp.49-62.
Mousavi, S.M. and Vahdani, B. (2016). Cross-docking location selection in distribution systems: a new intuitionistic fuzzy hierarchical decision model. International Journal of computational intelligence Systems, 9(1), pp.91-109.
Mousavi, S.M., Vahdani, B. and Abdollahzade, M. (2015). An intelligent model for cost prediction in new product development projects. Journal of Intelligent & Fuzzy Systems, 29(5), pp.2047-2057.
Mousavi, S.M., Vahdani, B. and Tavakkoli-Moghaddam, R. (2014a). Optimal design of the cross-docking in distribution networks: Heuristic solution approach. International Journal of Engineering, 27(4), pp.533-544.
Mousavi, S.M., Vahdani, B., Tavakkoli-Moghaddam, R. and Hashemi, H. (2014b). Location of cross-docking centers and vehicle routing scheduling under uncertainty: a fuzzy possibilistic–stochastic programming model. Applied Mathematical Modelling, 38(7-8), pp.2249-2264.
Mousavi, S.M. and Tavakkoli-Moghaddam, R. (2013). A hybrid simulated annealing algorithm for location and routing scheduling problems with cross-docking in the supply chain. Journal of Manufacturing Systems, 32(2), pp.335-347.
Mousavi, S.M., Tavakkoli-Moghaddam, R. and Jolai, F. (2013). A possibilistic programming approach for the location problem of multiple cross-docks and vehicle routing scheduling under uncertainty. Engineering Optimization, 45(10), pp.1223-1249.
Mousavi, S.M., Vahdani, B. and Behzadi, S.S. (2016). Designing a model of intuitionistic fuzzy VIKOR in multi-attribute group decision-making problems. Iranian Journal of Fuzzy Systems, 13(1), pp.45-65.
Niakan, F., Vahdani, B. and Mohammadi, M. (2015). A multi-objective optimization model for hub network design under uncertainty: An inexact rough-interval fuzzy approach. Engineering Optimization, 47(12), pp.1670-1688.
Nolte, I.M., Martin, E.C. and Boenigk, S. (2012). Cross-sectoral coordination of disaster relief. Public Management Review, 14(6), pp.707-730.
Noyan, N., Meraklı, M. and Küçükyavuz, S. (2017). Two-stage stochastic programming under multivariate risk constraints with an application to humanitarian relief network design. Mathematical Programming, pp.1-39.
Ransikarbum, K. and Mason, S.J. (2016). Multiple-objective analysis of integrated relief supply and network restoration in humanitarian logistics operations. International Journal of Production Research, 54(1), pp.49-68.
Saedinia, R., Vahdani, B., Etebari, F. and Nadjafi, B.A. (2019). Robust gasoline closed loop supply chain design with redistricting, service sharing and intra-district service transfer. Transportation Research Part E: Logistics and Transportation Review, 123, pp.121-141.
Shavarani, S. (2019), Multi-level facility location-allocation problem for post-disaster humanitarian relief distribution: A case study. Journal of Humanitarian Logistics and Supply Chain Management, Vol. 9 No. 1, pp. 70-81. https://doi.org/10.1108/JHLSCM-05-2018-0036.
Timajchi, A., Al-e-Hashem, S.M.M. and Rekik, Y. (2019). Inventory routing problem for hazardous and deteriorating items in the presence of accident risk with transshipment option. International Journal of Production Economics, 209, pp.302-315.
Vahdani, B., Niaki, S.T.A. and Aslanzade, S. (2017a). Production-inventory-routing coordination with capacity and time window constraints for perishable products: Heuristic and meta-heuristic algorithms. Journal of cleaner production, 161, pp.598-618.
Vahdani, B., Soltani, M., Yazdani, M. and Mousavi, S.M. (2017b). A three level joint location-inventory problem with correlated demand, shortages and periodic review system: Robust meta-heuristics. Computers & Industrial Engineering, 109, pp.113-129.
Vahdani, B., Behzadi, S.S., Mousavi, S.M. and Shahriari, M.R. (2016). A dynamic virtual air hub location problem with balancing requirements via robust optimization: Mathematical modeling and solution methods. Journal of Intelligent & Fuzzy Systems, 31(3), pp.1521-1534.
Vahdani, B., Veysmoradi, D., Noori, F. and Mansour, F. (2018a). Two-stage multi-objective location-routing-inventory model for humanitarian logistics network design under uncertainty. International journal of disaster risk reduction, 27, pp.290-306.
Vahdani, B., Veysmoradi, D., Shekari, N. and Mousavi, S.M. (2018b). Multi-objective, multi-period location-routing model to distribute relief after earthquake by considering emergency roadway repair. Neural Computing and Applications, 30(3), pp.835-854.
Vahdani, B., Zandieh, M. and Roshanaei, V. (2011). A hybrid multi-stage predictive model for supply chain network collapse recovery analysis: a practical framework for effective supply chain network continuity management. International Journal of Production Research, 49(7), pp.2035-2060.
Vahdani, B. (2014). Vehicle positioning in cell manufacturing systems via robust optimization. Applied Soft Computing, 24, pp.78-85.
Van Wassenhove, L.N. (2006). Humanitarian aid logistics: supply chain management in high gear. Journal of the Operational Research Society, 57(5), pp.475-489.
Veysmoradi, D., Vahdani, B., Sartangi, M.F. and Mousavi, S.M. (2018). Multi-objective open location-routing model for relief distribution networks with split delivery and multi-mode transportation under uncertainty. Scientia Iranica. Transaction E, Industrial Engineering, 25(6), pp.3635-3653.