Partial order analysis method for multiple criteria sensitivity

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  • 1. School of Business Administration, Liaoning Technical University, Huludao 125105, Liaoning, China
    2. Institute of Management Science and Engineering, Liaoning Technical University, Huludao 125105, Liaoning, China

Received date: 2021-11-23

  Online published: 2025-03-08

Copyright

, 2025, All rights reserved. Unauthorized reproduction is prohibited.

Abstract

The sensitivity analysis method of multiple criteria decision making is mainly constructed by weight perturbation. When weight assignment is difficult or disputes occur, the evaluation results are often not robust enough. Partial order sensitivity analysis takes decision function as objective function and weight space as constraint condition to establish programming problem, and constructs the partial order relationship between schemes with the help of extreme point set. Ultimately, Hasse diagram is used to express the possible change results and the sensitivity of schemes and indicators is obtained. By changing the weight space, the partial order method can construct a variety of sensitivity analysis methods suitable for global, local and finite. The example application shows that the partial order results of the three kinds of sensitivity analysis are completely consistent with the simulation results, which reflects the effectiveness and uniqueness of the partial order method.

Cite this article

Lizhu YUE, Liwei YAO, Yahua CUI, Ke XU . Partial order analysis method for multiple criteria sensitivity[J]. Operations Research Transactions, 2025 , 29(1) : 63 -76 . DOI: 10.15960/j.cnki.issn.1007-6093.2025.01.006

References

1 赵小娟, 叶云, 周晋皓, 等. 珠三角丘陵区耕地质量综合评价及指标权重敏感性分析[J]. 农业工程学报, 2017, 33 (8): 8- 10.
2 Xiao S , Lu Z , Xu L . A new effective screening design for structural sensitivity analysis of failure probability with the epistemic uncertainty[J]. Reliability Engineering & System Safety, 2016, 156, 1- 14.
3 蔡毅, 邢岩, 胡丹. 敏感性分析综述[J]. 北京师范大学学报(自然科学版), 2008, 44 (1): 9- 16.
4 邢会敏, 相诗尧, 徐新刚, 等. 基于EFAST方法的AquaCrop作物模型参数全局敏感性分析[J]. 中国农业科学, 2017, 50 (1): 64- 76.
5 Wainwright H M , Finsterle S , Zhou Q , et al. Modeling the performance of large-scale CO2 storage systems: A comparison of different sensitivity analysis methods[J]. International Journal of Greenhouse Gas Control, 2013, 17, 189- 205.
6 Mousivand A , Menenti M , Gorte B . Global sensitivity analysis of the spectral radiance of a soil-vegetation system[J]. Remote Sensing of Environment, 2014, 145 (5): 131- 144.
7 Sobol I M , Kucherenko S . A new derivative based importance criterion for groups of variables and its link with the global sensitivity indices[J]. Computer Physics Communications, 2010, 181 (7): 1212- 1217.
8 Sobol I M . On sensitivity estimation for nonlinear mathematical models[J]. Matematicheskoe Modelirovanie, 1990, 2 (1): 112- 118.
9 蒋艳, 岳超源. 方案排序对权重比例变化的敏感性分析[J]. 华中科技大学学报(自然科学版), 2002, 30 (8): 24- 27.
10 程平, 刘伟. 多属性群决策中一种基于主观偏好确定属性权重的方法[J]. 控制与决策, 2010 (11): 1645- 1650.
11 Xu E , Zhang H . Spatially-explicit sensitivity analysis for land suitability evaluation[J]. Applied Geography, 2013, 45 (45): 1- 9.
12 Bertsch V , Fichtner W . A participatory multi-criteria approach for power generation and transmission planning[J]. Annals of Operations Research, 2016, 245 (1/2): 177- 207.
13 Zhang D , Han X , Jiang C , et al. The interval PHI2 analysis method for time-dependent reliability[J]. Scientia Sinica, 2015, 45, 54- 61.
14 Zhang D , Han X , Jiang C , et al. Time-variant reliability analysis through response surface method[J]. Journal of Mechanical Design, 2017, 139 (4): 041404.
15 Lerche D , Bruggemann R , Sorensen P , et al. A comparison of partial order technique with three methods of multi-criteria analysis for ranking of chemical substances[J]. Journal of Chemical Information & Computer Sciences, 2002, 42 (5): 1086- 1098.
16 Brüggemann R , Patil G P . Ranking and Prioritization for Multi-indicator Systems[M]. New York: Springer, 2011.
17 岳立柱, 张志杰, 闫艳. 蕴含权重的偏序集多准则决策法[J]. 运筹与管理, 2018, 2, 26- 31.
18 岳立柱, 李良琼. 应用偏序集表示权重难以获知的TOPSIS模型[J]. 模糊系统与数学, 2017, 4, 167- 174.
19 Carlsen L , Bruggemann R . Accumulating partial order ranking[J]. Environmental Modelling & Software, 2008, 23, 986- 993.
20 Chen Y , Yu J , Khan S . Spatial sensitivity analysis of multi-criteria weights in GIS-based land suitability evaluation[J]. Environmental Modelling] & Software, 2010, 25 (12): 1582- 1591.
21 Rajabi A M . The stratified multi-criteria decision-making method[J]. Knowledge-Based Systems, 2018, 1- 9.
22 李焕欢, 纪颖, 屈绍建. 非对称成本环境下两阶段随机成本共识模型的研究[J]. 电子科技大学学报(社会科学版), 2022, 24 (2): 103- 112.
23 Lahdelma R , Hokkanen J , Salminen P . SMAA——Stochastic multi-objective acceptability analysis[J]. European Journal of Operational Research, 1998, 106 (1): 137- 143.
24 陈磊, 谢颖. 基于双参考点前景理论求解策略的DEA交叉效率评价方法[J]. 电子科技大学学报(社会科学版), 2021, 23 (06): 76- 81.
25 Ahn B S . Extreme point-based multi-attribute decision analysis with incomplete information[J]. European Journal of Operational Research, 2015, 240 (3): 748- 755.
26 Kaliszewski I , Podkopaev D . Simple additive weighting——A metamodel for multiple criteria decision analysis methods[J]. Expert Systems with Applications, 2016, 54, 155- 161.
27 Aggarwal M . Discriminative aggregation operators for multi criteria decision making[J]. Applied Soft Computing, 2017, 52, 1058- 1069.
28 范懿. 一个有关哈斯图的解析方法[J]. 上海第二工业大学学报, 2003, 1 (1): 17- 22.
29 高雅, 岳立柱, 周志强. 权重可变条件下员工绩效排名稳健性的Hasse图分析[J]. 运筹与管理, 2021, 30 (5): 208- 213.
30 徐振亭. 中小型民营企业员工绩效考核研究[D]. 沈阳: 沈阳大学, 2011.
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