no. 2
Allocating fixed resources for DMUs with interval data
RAIRO. Operations Research, Tome 55 (2021) no. 2, pp. 505-520

Conventional DEA models tend to allocate the fixed resources to multiple decision-making units (DMUs) and treat the allocated resource as an extra input for every single DMU. However, the existing DEA resource allocation (DEA-RA) methods are applicable exclusively to the DMUs with exact values of inputs and outputs. A lack of precision for the input or output data of DMUs, such as the interval data, would cause a failure of the existing methods to allocate resources to DMUs. In order to resolve this problem, three DEA-RA models are proposed in this paper for different scenarios of decision-making. All of the proposed DEA-RA models are based on a set of common weights. Finally, the proposed models are empirically tested and validated through three examples. As revealed by the results, our proposed models are capable of providing a more fair and practical initial allocation scheme for decision makers.

Reçu le :
Accepté le :
Première publication :
Publié le :
DOI : 10.1051/ro/2020142
Classification : 90-08, 91B32
Keywords: Resource allocation, interval data, efficiency 
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Sun, Jiasen; Chen, Meng; Fu, Yelin; Luo, Hao. Allocating fixed resources for DMUs with interval data. RAIRO. Operations Research, Tome 55 (2021) no. 2, pp. 505-520. doi: 10.1051/ro/2020142

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Note to the reader: The corresponding author has been corrected on April 5, 2021.