Multi-objective open location-routing model for relief distribution networks with split delivery and multi-mode transportation under uncertainty

In this study, the response phase of the management of natural disasters is investigated. One of the important issues in this phase is determining the distribution areas and timely distribution of relief to affected areas in which transportation routing is of a critical matter. In the event of disasters, especially flood and earthquake, terrestrial transportation is not that much easy due to the damage to many infrastructures. For this reason, we propose that delivering relief from the distribution areas to disaster stricken places should be done simultaneously by terrestrial as well as aerial transportation modes to increase route reliability and reduce travel time. In this study, for relief allocation after earthquake, we offer a mixed-integer nonlinear open location-routing model in uncertainty condition. This model includes several contradictory objectives and variety of factors such as travel time, total costs, and reliability. In order to solve this model, a hybrid solution by combining robust optimization and fuzzy multi-objective programming has been used. The performance and effectiveness of the offered model and solution approach has been investigated through a case study on the earthquake in East Azerbaijan, Iran. Our computational results show the solution we have offered for real problems has been effective.