A multi-objective mathematical model for optimization design of humanitarian logistics network using meta-heuristic algorithm: a model to enhance actors’ coordination

This research aims to optimize humanitarian logistics to increase coordination between actors in the phase during and after the disaster and aims to minimize the cost of relief, minimize the time of relief and minimize the cost of rebuilding infrastructure and housing for the affected people.

This research, in terms of the research direction types, is developmental because it is trying to expand the existing models in the design of the humanitarian logistics network and consider the optimization of two phases during the post-disaster phase. The proposed model has been solved using two metaheuristic algorithms named multi-objective genetic algorithm and multi-objective particle swarm optimization.

The implementation of this study will lead to a reduction in the costs of locating, routing and reconstruction in the humanitarian supply chain, as well as reducing the time of providing aid to the affected people and increasing their satisfaction. It is also possible to reduce the inventory of relief products with the help of this issue. Appropriate planning in humanitarian logistics processes, especially in the coordination phase of reconstruction, will be done according to the limited budget of governments and the appropriate use of resources.

Originality/Value: 

One of the innovations of this study is reducing the cost of reconstruction after an earthquake. Several studies were conducted in order to recover from the disaster. Over the past two decades, response phase relief operations have been the focus of a significant number of researchers. However, the issue of post-disaster recovery and reconstruction programs has not been sufficiently discussed in scientific and practical forums.