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A Variance Maximization Based Weight Optimization Method for Railway Transportation Safety Performance Measurement

Author

Listed:
  • Dongye Sun

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Yuanhua Jia

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Lingqiao Qin

    (Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA)

  • Yang Yang

    (School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China)

  • Juyong Zhang

    (School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China)

Abstract

Based on the idea of maximizing variances, a weight optimization method is proposed in this research to improve railway transportation safety evaluation. Firstly, the main evaluation indicators that can reflect the safety of railway transportation are selected as the independent variables. Secondly, in order to avoid the influence of experts’ empowerment on the evaluation results of railway transport safety, fuzzy set theory is introduced to generate the variation range of the weights of each evaluation index, which is used as the constraint of weight optimization model. Then, the weight optimization model for railway transportation safety performance measurement is established based on the principle of maximum variance. The structure of the optimization model shows the characteristics of the quadratic programming model. Therefore, the optimal weight is calculated by using the branch bounded algorithm, which is one of the quadratic programming model solution algorithms. Finally, the empirical analysis of the safety performance measurement for 18 railway bureaus shows that using the optimized index weight for safety performance measurement can not only make full use of prior information but also ensure that 18 railway bureaus can be distinguished to the maximum extent.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:8:p:2903-:d:164026
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    References listed on IDEAS

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    1. Ma, Jian & Fan, Zhi-Ping & Huang, Li-Hua, 1999. "A subjective and objective integrated approach to determine attribute weights," European Journal of Operational Research, Elsevier, vol. 112(2), pages 397-404, January.
    2. Dong, Yucheng & Liu, Yating & Liang, Haiming & Chiclana, Francisco & Herrera-Viedma, Enrique, 2018. "Strategic weight manipulation in multiple attribute decision making," Omega, Elsevier, vol. 75(C), pages 154-164.
    3. 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.
    4. Xu, Xiaozhan, 2004. "A note on the subjective and objective integrated approach to determine attribute weights," European Journal of Operational Research, Elsevier, vol. 156(2), pages 530-532, July.
    5. Zhang, Limao & Wu, Xianguo & Skibniewski, Miroslaw J. & Zhong, Jingbing & Lu, Yujie, 2014. "Bayesian-network-based safety risk analysis in construction projects," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 29-39.
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    Cited by:

    1. Nijole Batarliene, 2020. "Essential Safety Factors for the Transport of Dangerous Goods by Road: A Case Study of Lithuania," Sustainability, MDPI, vol. 12(12), pages 1-16, June.
    2. Yang Yang & Zhenzhou Yuan & Xin Fu & Yinhai Wang & Dongye Sun, 2019. "Optimization Model of Taxi Fleet Size Based on GPS Tracking Data," Sustainability, MDPI, vol. 11(3), pages 1-19, January.

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