A Variance Maximization Based Weight Optimization Method for Railway Transportation Safety Performance Measurement
Open Access
- 16 August 2018
- journal article
- research article
- Published by MDPI AG in Sustainability
- Vol. 10 (8) , 2903
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.Keywords
This publication has 23 references indexed in Scilit:
- AHP, Gray Correlation, and TOPSIS Combined Approach to Green Performance Evaluation of Design AlternativesIEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017
- Dynamic Case Retrieval Method With Subjective Preferences and Objective Information for Emergency Decision MakingIEEE/CAA Journal of Automatica Sinica, 2016
- Application of fuzzy fault tree analysis for evaluation of railway safety risks: an evaluation of root causes for passenger train derailmentProceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2011
- Incident tree model and incident tree analysis method for quantified risk assessment: An in-depth accident study in traffic operationSafety Science, 2010
- A subjective and objective integrated multiple attribute decision making method for material selectionMaterials & Design (1980-2015), 2010
- Developing a fuzzy TOPSIS approach based on subjective weights and objective weightsExpert Systems with Applications, 2009
- A note on the subjective and objective integrated approach to determine attribute weightsEuropean Journal of Operational Research, 2004
- A new accident model for engineering safer systemsSafety Science, 2004
- A subjective and objective integrated approach to determine attribute weightsEuropean Journal of Operational Research, 1999
- Risk assessment of a new high speed railwayQuality and Reliability Engineering International, 1995