ArticleAnnals of operations research2022
A robust multi-objective model for healthcare resource management and location planning during pandemics.
Article in Annals of operations research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Optimizing patient flow logistics: strategic challenges, tactical solutions, and future directions.BMC health services research · 2025Pooled it
- Optimizing Territorial Healthcare Networks with a Capacity-Constrained Hub-And-Spoke Allocation Algorithm: The Province of L'Aquila Case Study.Healthcare (Basel, Switzerland) · 2026Article
- A stochastic programming approach for dynamic allocation of bed capacity and assignment of patients to collaborating hospitals during pandemic outbreaks.Health care management science · 2026Article
- Dynamic demand forecasting and capacity assessment for emergency care system: a hybrid time series and machine learning approach with evidence from Beijing.BMC health services research · 2026Article
- Integrating epidemiological modeling and time-series forecasting to optimize pandemic patient allocation.International journal of health geographics · 2026Article
- From neglect to necessity: a community case study on the strategic recovery of 57 ventilators during the COVID-19 pandemic.Frontiers in health services · 2026Article
- Using AI to enhance healthcare resource management and allocation: A focus on the autism community in Alabama.PloS one · 2026Article
- Classification of medical imaging technologies: results from Türkiye.BMC health services research · 2025Article
- Decoding uncertainty for clinical decision-making.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- Risk-based allocation of COVID-19 personal protective equipment under supply shortages.European journal of operational research · 2023Article
- Data analytics during pandemics: a transportation and location planning perspective.Annals of operations research · 2022Article
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Authors and funding
3 authors.
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Abstract
In this study, we consider the problem of healthcare resource management and location planning problem during the early stages of a pandemic/epidemic under demand uncertainty. Our main ambition is to improve the preparedness level and response effectiveness of healthcare authorities in fighting pandemics/epidemics by implementing analytical techniques. Building on lessons from the Chinese experience in the COVID-19 outbreak, we first develop a deterministic multi-objective mixed integer linear program (MILP) which determines the location and size of new pandemic hospitals (strategic level planning), periodic regional health resource re-allocations (tactical level planning) and daily patient-hospital assignments (operational level planning). Taking the forecasted number of cases along a planning horizon as an input, the model minimizes the weighted sum of the number of rejected patients, total travel distance, and installation cost of hospitals subject to real-world constraints and organizational rules. Next, accounting for the uncertainty in the spread speed of the disease, we employ an across scenario robust (ASR) model and reformulate the robust counterpart of the deterministic MILP. The ASR attains relatively more realistic solutions by considering multiple scenarios simultaneously while ensuring a predefined threshold of relative regret for the individual scenarios. Finally, we demonstrate the performance of proposed models on the case of Wuhan, China. Taking the 51 days worth of confirmed COVID-19 case data as an input, we solve both deterministic and robust models and discuss the impact of all three level decisions to the quality and performance of healthcare services during the pandemic. Our case study results show that although it is a challenging task to make strategic level decisions based on uncertain forecasted data, an immediate action can considerably improve the response effectiveness of healthcare authorities. Another important observation is that, the installation times of pandemic hospitals have significant impact on the system performance in fighting with the shortage of beds and facilities.
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