Title: A new approach on the lowest cost problem in data envelopment analysis

Authors: Xu Wang; Kuan Lu; Takashi Hasuike

Addresses: Department of Industrial and Management Systems Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan ' NCE CTO Office, Huawei Technologies Co., Ltd., No. 165 Beiqing Rd, Z-park, Hai Dian Dist., Beijing 100094, China ' Department of Industrial and Management Systems Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan

Abstract: This paper aims at solving the lowest cost problem in data envelopment analysis (DEA), which is to provide an efficient target for an inefficient decision making unit (DMU) with the lowest adjustment costs. For this purpose, a new approach based on the least distance DEA model is proposed. Here, the marginal costs of adjusting the inputs and outputs are assumed to be known and symmetrical. For the practical merit, different with the existing studies, our approach is able to increase inputs and decrease outputs. Numerical experiments are conducted to compare the performance of the proposed approach with previous existing studies. The results show that the proposed approach can always provide an efficient target with no higher total adjustment costs than the costs of targets provided by previous approaches. Thus, the proposed approach is more practical and useful.

Keywords: data envelopment analysis; DEA; lowest cost problem; least distance model; symmetrical marginal costs.

DOI: 10.1504/AJMSA.2021.118423

Asian Journal of Management Science and Applications, 2021 Vol.6 No.1, pp.69 - 84

Received: 16 Jan 2021
Accepted: 16 May 2021
Published online: 25 Oct 2021 *

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