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An Input-Output Orientation Model for Estimating Most Productive Scale Size in Fuzzy Data Envelopment Analysis

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Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2020)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 88))

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Abstract

This paper presents a new input-output orientation data envelopment analysis (DEA) model for estimating most productive scale size (MPSS) based on possibility measure, in which the inputs and outputs are assumed to be represented by fuzzy variables with known membership functions. When the fuzzy inputs and outputs are trapezoidal fuzzy variables, the proposed model is transformed into its equivalent linear programming form. Furthermore, the sensitivity analysis of the proposed model are discussed. At last, to illustrate the application of the proposed method, fuzzy data of 12 flexible manufacturing systems (FMSs) are used to determine which FMS is possibilistic MPSS.

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Authors and Affiliations

  1. Institute of Applied Mathematics, Army Engineering University, Shijiazhuang Division, Shijiazhuang, 050003, China

    Mingqiang Meng & Lihong Liu

Authors
  1. Mingqiang Meng
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  2. Lihong Liu
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Editor information

Editors and Affiliations

  1. College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, UK

    Hongying Meng

  2. School of Electronical Information and Artificial Engineering, Shaanxi University of Science and Technology, Xi’an, China

    Tao Lei

  3. College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, UK

    Maozhen Li

  4. College of Electrical and Information, Hunan University, Changsha, China

    Kenli Li

  5. Division of Intelligent Future Technologies, Mälardalen University, Västerås, Västmanlands Län, Sweden

    Ning Xiong

  6. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Lipo Wang

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Meng, M., Liu, L. (2021). An Input-Output Orientation Model for Estimating Most Productive Scale Size in Fuzzy Data Envelopment Analysis. In: Meng, H., Lei, T., Li, M., Li, K., Xiong, N., Wang, L. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2020. Lecture Notes on Data Engineering and Communications Technologies, vol 88. Springer, Cham. https://doi.org/10.1007/978-3-030-70665-4_81

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