Vehicle routing problem for humanitarian relief distribution under hybrid uncertainty

Abstract

Purpose

Given the importance of estimating the demand for relief items in earthquake disaster, this research studies the complex nature of demand uncertainty in a vehicle routing problem in order to distribute first aid relief items in the post disaster phase, where routes are subject to disruption.

Design/methodology/approach

To cope with such kind of uncertainty, the demand rate of relief items is considered as a random fuzzy variable and a robust scenario-based possibilistic-stochastic programming model is elaborated. The results are presented and reported on a real case study of earthquake, along with sensitivity analysis through some important parameters.

Findings

The results show that the demand satisfaction level in the proposed model is significantly higher than the traditional scenario-based stochastic programming model.

Originality/value

In reality, in the occurrence of a disaster, demand rate has a mixture nature of objective and subjective and should be represented through possibility and probability theories simultaneously. But so far, in studies related to this domain, demand parameter is not considered in hybrid uncertainty. The worth of considering hybrid uncertainty in this study is clarified by supplementing the contribution with presenting a robust possibilistic programming approach and disruption assumption on roads.

Citation

Nodoust, S., Pishvaee, M.S. and Seyedhosseini, S.M. (2023), "Vehicle routing problem for humanitarian relief distribution under hybrid uncertainty", Kybernetes, Vol. 52 No. 4, pp. 1503-1527. https://doi.org/10.1108/K-09-2021-0839