Assessing Trade‐offs among Multiple Objectives for Humanitarian Aid Delivery Using Expert Preferences

TLDR

Humanitarian aid agencies deliver emergency supplies and services to disaster‑affected populations, yet existing modeling approaches lack validated trade‑offs among multiple delivery goals. The study develops a method to evaluate aid delivery plans using expert preferences across five key attributes: cargo volume, commodity prioritization, location prioritization, delivery speed, and operational cost. A conjoint analysis survey of 18 experienced humanitarian logisticians quantified attribute importance, producing a piecewise linear utility function for use in optimization models. The survey revealed that cargo volume is the most valued objective, cost the least, and that experts prioritize vulnerable communities and critical commodities while still considering others, enabling improved objective functions for aid delivery.

Abstract

Humanitarian aid agencies deliver emergency supplies and services to people affected by disasters. Scholars and practitioners have developed modeling approaches to support aid delivery planning, but they have used objective functions with little validation as to the trade‐offs among the multiple goals of aid delivery. We develop a method to value the performance of aid delivery plans based on expert preferences over five key attributes: the amount of cargo delivered, the prioritization of aid by commodity type, the prioritization of aid by delivery location, the speed of delivery, and the operational cost. Through a conjoint analysis survey, we measure the preferences of 18 experienced humanitarian logisticians. The survey results quantify the importance of each attribute and enable the development of a piecewise linear utility function that can be used as an objective function in optimization models. The results show that the amount of cargo delivered is the most valued objective and cost the least important. In addition, experts prioritize more vulnerable communities and more critical commodities, but not to the exclusion of others. With these insights and the experts’ utility functions, better humanitarian objective functions can be developed to enable better aid delivery in emergency response.