Designing an efficient humanitarian supply chain network during an emergency: A scenario-based multi-objective model

Efficient humanitarian supply chain (HSC) management plays an underlying role in saving lives, reducing human torment, and contributing to sustainable development during a disaster. Accordingly, the issue of locating and allocating relief facilities in the first hours after the occurrence of a disaster has a great impact on providing timely service. This study addresses a sustainable location-allocation-inventory problem (LAIP) to design an efficient HSC through concurrently optimizing four objectives of fairness, timeliness, economic productivity, and social justice. To do so, a novel scenario-based multi-objective mixed-integer linear programming (MILP) model is developed to formulate the problem under uncertainty. According to this model, the process of taking care of injured people is carried out in three stages of decision-making. Maximum facilities for sending relief supplies are used to supply the demand at each stage. In addition, the three factors of supply, demand, and communication routes between the centers and the affected areas are defined as fuzzy random parameters. Since the proposed model contains multiple objectives, goal programming (GP) is applied to provide a single-objective model. The validation of the developed methodology is made with the help of an illustrative example in the literature, and the results are obtained and evaluated using sensitivity analysis of the objective functions’ weights. As one of the main findings, sending the maximum available supplies in MDCs to the affected areas in three stages using surplus vehicles is the best solution to cover the shortage of products. Finally, it is revealed that the proposed methodology can be utilized by managers to tackle the complexity of the problem during natural disasters.