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A cooperative robust human resource allocation problem for healthcare systems for disaster management
•A cooperative robust resource allocation and demand distribution model is developed.•Behaviors of hospitals are appraised by a mixed integer linear programming formulation.•Performance of models are evaluated based on post-disaster circumstances.•Payoffs are distributed among hospitals by cooperati...
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Published in: | Computers & industrial engineering 2022-08, Vol.170, p.108283, Article 108283 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •A cooperative robust resource allocation and demand distribution model is developed.•Behaviors of hospitals are appraised by a mixed integer linear programming formulation.•Performance of models are evaluated based on post-disaster circumstances.•Payoffs are distributed among hospitals by cooperative game theory methods.
Similar to other human-made institutes, healthcare systems often experience post-disaster disruptions in performance, which can pose significant threats to the people’s lives in the affected zone. In this study, we develop a cooperative game theory approach to alleviate the negative impacts of such catastrophic events, minimize normal hospital service levels, and reduce undesired expenses. Hence, we propose a linear robust formulation to enable the observation of collaborative behaviors among medical centers, including transferring staff, beds, and patients between hospitals. In our proposed model, information uncertainty is considered the right-hand side parameter (i.e., as coefficients for the decision variables of the constraints). Moreover, the existence of a core in the developed game structure is investigated to demonstrate the stability of the developed cooperative structure. Finally, we generated many numerical examples to evaluate the performance of the model under various circumstances and presented a number of managerial insights. |
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ISSN: | 0360-8352 1879-0550 |
DOI: | 10.1016/j.cie.2022.108283 |