Work

Multi-period disaster relief supplies allocation considering horizontal reference and inequity aversion in disaster-affected areas

Year: 2026

Type: article

Abstract: To address the challenges of limited relief supplies, urgent demand, and potential distribution disparities among disaster-affected areas, this study develops a multi-period relief supplies allocation model comprising a single emergency response center and multiple affected sites. To capture the non-linear characteristics of human suffering, the model incorporates deprivation costs arising from unsatisfied demands using an exponential function. Drawing on the peer-induced reference theory by Ho and Su, we introduce horizontal comparisons among affected areas. Furthermore, the Fehr-Schmidt inequity aversion model is integrated to quantify the utility losses associated with both advantageous and disadvantageous inequities. Consequently, a multi-period non-linear programming model is formulated, incorporating supply capacity, demand, and state transition constraints. A rolling horizon non-linear programming algorithm is designed to solve the model efficiently. Case study results based on the 2021 Henan extreme rainstorm disaster demonstrate that, compared to the baseline model focusing solely on deprivation costs, incorporating horizontal comparisons and inequity aversion significantly improves distribution equity under resource scarcity, reducing both the maximum per capita disparity and the Gini coefficient. Ablation experiments reveal that advantageous and disadvantageous inequity aversion play distinct roles in preventing resource over-concentration and safeguarding vulnerable areas, respectively; their synergy establishes a stable trade-off between deprivation costs and distributional equity. Sensitivity analysis indicates that while fairness preference intensity and deprivation cost parameters influence the allocation outcomes and the efficiency-equity trade-off, the model consistently maintains feasibility and convergence across various parameter settings. Furthermore, large-scale computational experiments validate the scalability and robustness of the model under extensive disaster scenarios. This study provides valuable decision-making support for multi-period humanitarian logistics scheduling, balancing demand satisfaction and social equity under severe resource constraints.

Source: Sustainable Futures

DOI: 10.1016/j.sftr.2026.102175

Authors: Lina Yu, Jinghe Zhou, Huailin Ke, Huawei Zheng, Yinlian Zeng, Qiang Li

Institutions: Shenzhen Technology University, Shenzhen University

Language: English

Topic: Facility Location and Emergency Management

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: No poverty, Reduced inequalities

Open Access status: gold

Estimated APC paid: $2,340