Goal programming optimization model under uncertainty and the critical areas characterization in humanitarian logistics management

The purpose of this paper is to improve disaster management models, have an optimal distribution of assets, reduce human suffering in a crisis and find a good solution for warehouse locations, distribution points, inventory levels and costs, considering the uncertainty of a wide range of variables, to serve as a support model for decision making in real situations.

A model is developed based on the recent models. It includes structured and non-structured data (historical knowledge) from a humanitarian perspective. This model considers the uncertainty in a landslide and flood area and it is applied in a representative Peruvian city.

The proposed model can be used to determine humanitarian aid supply and its distribution with uncertainty, regarding the affected population and its resilience. This model presents a different point of view from the efficiency of the logistics perspective, to identify the level of trust between all the stakeholders (public, private and academic). The finding provides a new insight in disaster management to cover the gap between applied research and human behavior in crisis.

In this study the access of reliable information is limited.

This paper provides an operation model with uncertainty in a humanitarian crisis and a decision-making tool with some recommendation for further public policies.

This study presents a model for decision makers in a low-income zone and highlights the importance of preparedness in the humanitarian system. This paper expands the discussion of how the mathematical models and human behaviors interact with different perspectives in a humanitarian crisis.