Sustainability and intermodality in humanitarian logistics: a two-stage multi-objective programming formulation

When managing crises and disasters, decision-makers face high uncertainty levels, disrupted supply chains, and damaged infrastructure. This complicates delivering resources that are essential for the survival of the victims. Flexible and adaptable supply networks are needed to ensure a consistent flow of relief to the areas affected by disasters. Intermodality is a valuable approach when infrastructure is damaged, as it allows the use of different delivery modes to reach demand areas. Nevertheless, involving different transportation modes has an impact on the environment. Looking at the importance of helping victims and considering the environmental impact of humanitarian operations for long-term sustainability, intermodality and carbon emission reduction measures can be an interesting combination. This area, however, is currently understudied. This article introduces a two-stage stochastic formulation to fill that gap. The model addresses facility location, resource allocation, and intermodal relief distribution considering carbon emission reduction in facilities, intermodal activities, and distribution. The formulation minimises costs and the level of shortage of relief. The model is tested using a case study in Sinaloa, Mexico, to investigate the impact of intermodality and carbon emission reduction measures on costs and shortage of relief for disaster victims. The findings confirm that the model proposed allows for the diversification of transportation modes and reduces carbon emissions whilst achieving a good level of performance in both metrics. The comparison with a benchmark model without intermodality and carbon reduction measures suggests that the formulation can increase flexibility and reduce the level of CO2 emissions whilst maintaining high satisfaction rates.