Designing a cross docking-based humanitarian supply chain network using a meta-heuristic algorithm.

In present study, a mathematical model for designing a humanitarian supply chain network and vehicle routing problem considering cross-dock is proposed where a Non-dominated Sorting Genetic Algorithm (NSGAIII) is used for implementing the proposed model in a large-scale problem. Since the model was implemented in a large-scale case, various sensitivity analyses were performed to extract the results. Hence, the results showed that the costs have more effect on the first objective function (patients compared to total injuries) and the second one (shortage), respectively. Compared to the other two objective functions, the impact on the cost function is negligible. The effect of transportation cost of relief goods/supplies from the supplier to the warehouse on the first objective function is higher than the others; however, the effect of this cost is further than that of the cost from the supplier to the distributor, accordingly, in comparison to the previous cost, the output reacted more to this cost. The transportation cost from the distributor to the warehouse (cross-docking) has less effect on the cost function unlike the transportation cost from the supplier to the warehouse. Nevertheless, the result shows that an increase in the cost can lead to a considerable increase in the ratio of patients to total injuries as well as shortage. In other words, the objective functions would deteriorate when this parameter tends to be increased.