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A three-stage hybrid approach for weight assignment in MADM

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  • Yang, Guo-liang
  • Yang, Jian-Bo
  • Xu, Dong-Ling
  • Khoveyni, Mohammad

Abstract

How to determine weights for attributes is one of the key issues in multiple attribute decision making (MADM). This paper aims to investigate a new approach for determining attribute weights based on a data envelopment analysis (DEA) model without explicit inputs (DEA-WEI) and minimax reference point optimisation. This new approach first considers a set of preliminary weights and the most favourite set of weights for each alternative or decision making unit (DMU) and then aggregates these weight sets to find the best compromise weights for attributes with the interests of all DMUs taken into account fairly and simultaneously. This approach is intended to support the solution of such MADM problems as performance assessment and policy analysis where (a) the preferences of decision makers (DMs) are either unclear and partial or difficult to acquire and (b) there is a need to consider the best "will" of each DMU. Two case studies are conducted to show the property of this new proposed approach and how to use it to determine weights for attributes in practice. The first case is about the assessment of research strengths of EU-28 member countries under certain measures and the second is for analysing the performances of Chinese Project 985 universities, where the weights of the attributes need to be assigned in a fair and unbiased manner.

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  • Yang, Guo-liang & Yang, Jian-Bo & Xu, Dong-Ling & Khoveyni, Mohammad, 2017. "A three-stage hybrid approach for weight assignment in MADM," Omega, Elsevier, vol. 71(C), pages 93-105.
    • Handle: RePEc:eee:jomega:v:71:y:2017:i:c:p:93-105
    DOI: 10.1016/j.omega.2016.09.011
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    4. Yang, Guo-liang & Fukuyama, Hirofumi & Song, Yao-yao, 2018. "Measuring the inefficiency of Chinese research universities based on a two-stage network DEA model," Journal of Informetrics, Elsevier, vol. 12(1), pages 10-30.
    5. Feng Li & Qingyuan Zhu & Liang Liang, 2019. "A new data envelopment analysis based approach for fixed cost allocation," Annals of Operations Research, Springer, vol. 274(1), pages 347-372, March.
    6. Dongye Sun & Yuanhua Jia & Lingqiao Qin & Yang Yang & Juyong Zhang, 2018. "A Variance Maximization Based Weight Optimization Method for Railway Transportation Safety Performance Measurement," Sustainability, MDPI, vol. 10(8), pages 1-13, August.
    7. Song, Yongming & Li, Yanhong & Zhu, Hongli & Li, Guangxu, 2023. "A decision support model for buying battery electric vehicles considering consumer learning and psychological behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
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    9. Chao Sun & Shiying Li & Yong Deng, 2020. "Determining Weights in Multi-Criteria Decision Making Based on Negation of Probability Distribution under Uncertain Environment," Mathematics, MDPI, vol. 8(2), pages 1-15, February.

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