Allocating fixed resources for DMUs with interval data

¹ Research Center for Smarter Supply Chain, School of Business & Dongwu Think Tank, Soochow University, No. 50, Donghuan Road, Suzhou, RJ, China
² School of Intelligent Systems Science and Engineering, Jinan University (Zhuhai Campus), Zhuhai, China
³ Department of Industrial & Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, China
⁴ College of Economics, Shenzhen University, Shenzhen, China

^* Corresponding author: msylfu@gmail.com

Received: 23 October 2016
Accepted: 17 December 2020

Abstract

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.