Designing a humanitarian logistics network for location-routing equipped with drone-enabled delivery systems under uncertainty conditions

This study aims to design a humanitarian logistics network for location-routing equipped with drone-enabled delivery systems under uncertainty conditions. Here, we divided the model into two phases including pre- and post-disaster. There is an important question in pre-disaster phase: Where the central warehouses better perform to minimize the cost and time? To this end, the logistics problem represented by the transportation of relief products was modeled as a Multi Echelon Multiple Depot Vehicle Routing Problem (MEMDVRP). For solving this mathematical problem, the presented model was initially solved using meta-heuristic algorithm of Non-dominated Sorting Genetic Algorithm III (NSGAIII) in large dimensions and sensitivity analysis was performed on its effective parameters via MATLAB software. Due to the scenario nature of the problem, 4 scenarios were considered in the model and then were compared separately for each goal. Given the results, scenario 4 showed the best situation in terms of benefits maximization. Regarding the cost, scenario 4 shows the worst status and the scenarios 1 and 2 revealed the best status. It should be noted that due to the nature of cost minimization objective, the lower this value, the better the result, indicating the best cost situation for Scenarios 1 and 2 and the worst for scenario 4. In terms of time, Scenario 4 indicated the worst condition likewise the cost. Interestingly, regarding the benefits, the Scenario 4 leads to the most benefits, so it can be said that in this scenario, as the benefits increase, the cost and time also increase, suggesting a conflict in objectives.