Modeling equitable and effective distribution problem in humanitarian relief logistics by robust goal programming

Abstract

Humanitarian relief food distribution problem is the pickup of the food supply from different donors and the distribution to individuals in need. The problem now becomes a meaningful work to alleviate people’s bad situations. Motivated by this prevalent steam of significant topic, we focus on the humanitarian relief problem. In this paper, we examine the equitable and effective food distribution to poor people who need food in the general poverty scenario. In the modeling process, we make a classification of the demand nodes. Then, we introduce an innovative robust goal programming model with priority factors and optimize the distribution decisions under uncertain supply and capacity characterized by an uncertainty set. Under robust optimization techniques, the solving process of our proposed robust model is discussed and depends on a parametric cone program which can be efficiently solved by the commercial software. Finally, we conduct a number of numerical experiments about the Food Bank of Central and Eastern North Carolina in America to illustrate the application of our new model. The computational results show that our model can realize the trade-off between equity and effectiveness under uncertainty for humanitarian relief problem.