考虑信息源相关性的多属性应急决策方法

陈雪龙, 王亚丽

系统工程理论与实践 ›› 2018, Vol. 38 ›› Issue (8) : 2045-2056.

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系统工程理论与实践 ›› 2018, Vol. 38 ›› Issue (8) : 2045-2056. DOI: 10.12011/1000-6788(2018)08-2045-12
论文

考虑信息源相关性的多属性应急决策方法

    陈雪龙, 王亚丽
作者信息 +

The method for multi-attribute emergency decision-making considering the interdependence between information sources

    CHEN Xuelong, WANG Yali
Author information +
文章历史 +

摘要

利用证据理论处理多属性应急决策时,通常假设信息源独立,有悖于现实情况.因此,提出考虑信息源相关性的多属性应急决策方法.首先,给出基于证据理论的多属性应急决策问题表示;其次,提出信息源相关程度的计算方法及考虑信息源相关度的证据合成规则,以融合证据信息;再次,给出基于Pignistic概率值的应急备选方案选择方法,扩大各方案之间的信度差异,以实现多属性应急决策的目的.最后,通过算例分析验证该方法在多属性应急决策中的有效性.分析结果表明,考虑信息源之间的相关性不仅使应急决策结果更加客观,同时弱化了证据理论有关信息源独立性的假设,扩大了其在实际应用中的范围.

Abstract

When evidence theory is applied to emergency decision-making, it is often supposed that the information sources are independent which is contrary to the reality. Therefore, we propose the method for multi-attribute emergency decision-making considering the interdependence between information sources. Firstly, the multi-attribute emergency decision-making problem is represented based on evidence theory. Secondly, we put forward the method to compute the interdependent degree between information sources, and the evidence combination rule considering the interdependent degree between information sources to fuse the evidence information. Thirdly, the emergency alternative selection method based on the Pignistic probability, which can expand the difference of alternatives' reliability, is discussed. At last, an example analysis on multi-attribute emergency decision-making problem is applied to verify the effectiveness of the proposed method. The analysis results show that considering the interdependence between information sources will make the emergency decision-making more objective and scientific, as well as weaken the independence hypothesis on information sources and expand the application scope of evidence theory.

关键词

应急 / 多属性决策 / 证据理论 / 信息源相关性

Key words

emergency / multi-attribute decision-making / evidence theory / interdependence of information sources

引用本文

导出引用
陈雪龙 , 王亚丽. 考虑信息源相关性的多属性应急决策方法. 系统工程理论与实践, 2018, 38(8): 2045-2056 https://doi.org/10.12011/1000-6788(2018)08-2045-12
CHEN Xuelong , WANG Yali. The method for multi-attribute emergency decision-making considering the interdependence between information sources. Systems Engineering - Theory & Practice, 2018, 38(8): 2045-2056 https://doi.org/10.12011/1000-6788(2018)08-2045-12
中图分类号: C934   

参考文献

[1] 刘奕,许伟,乔晗,等. 突发事件应急管理方法研究进展专辑序言[J]. 管理评论, 2016, 28(8):3-5.Liu Y, Xu W, Qiao H, et al. A preface to the progress of research on emergency management of emergencies[J]. Management Review, 2016, 28(8):3-5.
[2] 钟永光,毛中根,翁文国,等. 非常规突发事件应急管理研究进展[J]. 系统工程理论与实践, 2012, 32(5):911-918.Zhong Y G, Mao Z G, Weng W G, et al. Progress of "study on unconventional emergencies management"[J]. Systems Engineering-Theory & Practice, 2012, 32(5):911-918.
[3] Levy J K, Taji K. Group decision support for hazards planning and emergency management:A group analytic network process (GANP) approach[J]. Mathematical and Computer Modeling, 2007, 46(7):906-917.
[4] 邬文帅,寇刚,彭怡,等. 面向突发事件的模糊多目标应急决策方法[J]. 系统工程理论与实践, 2012, 32(6):1298-1304.Wu W S, Kou G, Peng Q, et al. A fuzzy multi-criteria emergency decision-making method[J]. Systems Engineering-Theory & Practice, 2012, 32(6):1298-1304.
[5] 孙秉珍,马卫民,赵海燕. 基于双论域模糊粗糙集的应急决策模型与方法[J]. 运筹与管理, 2014, 23(2):41-48.Sun B Z, Ma W M, Zhao H Y. The model and approach of emergency decision-making based on fuzzy rough set over two universes[J]. Operations Research and Management Science, 2014, 23(2):41-48.
[6] 吴凤平,程铁军.不确定环境下突发事件动态应急决策研究[J]. 软科学, 2014, 28(3):26-29.Wu F P, Cheng T J. Dynamic decision support for emergency response under uncertain environment[J]. Soft Science, 2014, 28(3):26-29.
[7] 管清云,陈雪龙,王延章. 基于距离熵的应急决策层信息融合方法[J]. 系统工程理论与实践, 2015, 35(1):216-227.Guan Q Y, Chen X L, Wang Y Z. Distance entropy based decision-making information fusion method[J]. Systems Engineering-Theory & Practice, 2015, 35(1):216-227.
[8] Dempster A P. Upper and lower probabilities induced by a multivalued mapping[J]. Annals of Mathematical Statistics, 1967, 38(2):325-339.
[9] Shafer G. A mathematical theory of evidence[M]. Princeton:Princeton University Press, 1976.
[10] 谭鑫,王炜,张茂军.不完备信息条件下基于证据理论的CGF行为决策方法[J]. 系统工程理论与实践, 2013, 33(6):1608-1614.Tan X, Wang W, Zhang M J. Behavior decision method of CGF with incomplete information based on evidence theory[J]. Systems Engineering-Theory & Practice, 2013, 33(6):1608-1614.
[11] 郭凯红,李文立. 权重信息未知情况下的多属性群决策方法及其拓展[J]. 中国管理科学, 2011, 19(5):94-103.Guo K H, Li W L. A method for multiple attribute group decision making with complete unknown weight information and its extension[J]. Chinese Journal of Management Science, 2011, 19(5):94-103.
[12] 郭凯红,李文立. 基于证据推理的不确定多属性决策方法[J]. 管理工程学报, 2012, 26(2):94-100.Guo K H, Li W L. Evidential reasoning-based approach for multiple attribute decision making problems under uncertainty[J]. Journal of Industrial Engineering and Engineering Management, 2012, 26(2):94-100.
[13] Yang J B, Xu D L. On the evidential algorithm for multiple attribute decision analysis under uncertainty[J]. IEEE Transactions on System, Man and Cybertics, Part A:System and Humans, 2002, 32(3):289-304.
[14] Xu D, Yang B, Wang Y. The evidential reasoning approach for multi-attribute decision analysis under interval uncertainty[J]. European Journal of Operational Research, 2006, 174(3):1914-1943.
[15] Guo M, Yang J B, Chin K S, et al. Evidential reasoning based preference programming for multiple attribute decision analysis under uncertainty[J]. European Journal of Operational Research, 2007, 182(3):1294-1312.
[16] Beynon M J. DS/AHP method:A mathematical analysis, including an understanding of uncertainty[J]. European Journal of Operation Research, 2002, 140(1):148-164.
[17] Hua Z, Gong B, Xu X. A DS-AHP approach for multi-attribute decision making problem with incomplete information[J]. Expert Systems with Applications, 2008, 34(3):2221-2227.
[18] Ju Y, Wang A. Emergency alternative evaluation under group decision makers:A method of incorporating DS/AHP with extended TOPSIS[J]. Expert Systems with Applications, 2012, 39(1):1315-1323.
[19] 孙怀江, 杨静宇.一种相关证据合成方法[J]. 计算机学报, 1999, 22(9):1004-1007.Sun H J, Yang J Y. A combination method for dependent evidences[J]. Chinese Journal of Computers, 1999, 22(9):1004-1007.
[20] 王进, 孙怀江. 一种DSm理论相关证据模型[J]. 计算机科学, 2009, 36(8):260-263.Wang J, Sun H J. Model for dependent evidences in DSmT framework[J]. Computer Science, 2009, 36(8):260-263.
[21] 肖文, 王正友,王耀德. 一种相关证据的合成规则[J]. 控制与决策, 2011, 26(5):773-776.Xiao W, Wang Z Y, Wang Y D. Combination rule for dependent evidences[J]. Control and Decision, 2011, 26(5):773-776.
[22] Su X, Mahadevan S, Han W, et al. Combining dependent bodies of evidence[J]. Applied Intelligence, 2016, 44(3):634-644.
[23] 杨善林,朱卫东,任明仑. 基于可变参数优化的相关证据合成方法研究[J]. 管理科学学报, 2003, 6(5):12-16.Yang S L, Zhu W D, Ren M L. Combination theory and method for interrelated evidences based optimal adjustment coefficient[J]. Journal of Management Sciences in China, 2003, 6(5):12-16.
[24] 陈莉. 基于粒子群神经网络优化的相关证据合成及应用[J]. 系统仿真学报, 2009, 21(3):711-715.Chen L. Related evidence synthesis based on particle swarm optimization neural network parameter and application[J]. Journal of System Simulation, 2009, 21(3):711-715.
[25] Denoeux T. Conjunctive and disjunctive combination of belief functions induced by non-distinct bodies of evidence[J]. Artificial Intelligence, 2008, 172(2-3):234-264.
[26] Guralnik V, Mylaraswamy D, Voges H. On handling dependent evidence and multiple faults in knowledge fusion for engine health management[C]//Aerospace Conference, 2006 IEEE, Big Sky, MT, 2006:9-17.
[27] Yager R R. On the fusion of non-independent belief structures[J]. International Journal General Systems, 2009, 38(5):505-531.
[28] Su X, Mahadevan S, Xu P, et al. Handling of dependence in Dempster-Shafer theory[J]. International Journal of Intelligent Systems, 2015, 30(4):441-467.
[29] Chebbah M, Martin A, Yaghlane B B. Combining partially independent belief functions[J]. Decision Support Systems, 2015, 73(C):37-46.
[30] Smets P, Kennes R. The transferable belief model[J]. Artificial Intelligence, 1994, 66(2):191-234.
[31] Saaty T L. A scaling method for priorities in hierarchical structure[J]. Journal of Mathematical Psychology, 1977, 15(3):237-281.
[32] 孙宏才,徐关尧,田平. 用网络层次分析法(ANP)评估应急桥梁设计方案[J]. 系统工程理论与实践, 2007, 27(3):63-70.Sun H C, Xu G Y, Tian P. Design alternatives evaluation of emergency bridge by applying analytic network process (ANP)[J]. Systems Engineering-Theory & Practice, 2007, 27(3):63-70.
[33] 赵萌,任嵘嵘,李刚. 基于模糊熵-熵权法的混合多属性决策方法[J]. 运筹与管理, 2013, 22(6):78-83.Zhao M, Ren R R, Li G. Method based on fuzzy entropy-entropy weight for hybird multi-attribute decision making[J]. Operations Research and Management Science, 2013, 22(6):78-83.
[34] Liu D R, Shih Y Y. Integrating AHP and data mining for product recommendation based on customer lifetime value[J]. Information and Management, 2005, 42(3):387-400.
[35] Amiri M P. Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods[J]. Expert Systems with Applications, 2010, 37(9):6218-6224.
[36] Dubois D, Prade H. Representation and combination of uncertainty with belief functions and possibility measures[J]. Computational Intelligence, 1988, 4(3):244-264.
[37] Martin A, Osswald C. Toward a combination rule to deal with partial conflict and specificity in belief functions theory[C]//International Conference on Information Fusion, Québec, Canada, 2007:1-8.
[38] Murphy C K. Combining belief functions when evidence conflicts[J]. Decision Support System, 2000, 29(1):1-9.
[39] Yager R R. On the Dempster-Shafer framework and new combination rules[J]. Information Science, 1987, 41(2):93-137.
[40] Lefévre E, Elouedi Z. How to preserve the conflict as an alarm in the combination of belief functions[J]. Decision Support System, 2013, 56(1):326-333.
[41] Smets P. The canonical decomposition of a weighted belief[C]//International Joint Conference on Artificial Intelligence, Morgan Kaufman, Montréal, Québec, Canada, 1995:1896-1901.
[42] Smith C A B. Consistency in statistical inference and decision[J]. Journal of the Royal Statistical Society, 1961, 23(1):1-37.
[43] Smets P. Constructing the pignistic probability function in a context of uncertainty[J]. Machine Intelligence & Pattern Recognition, 1990, 10:29-39.
[44] 陈圣群, 王应明. 区间值信念结构下冲突证据组合[J]. 系统工程理论与实践, 2014, 34(1):256-261.Chen S Q, Wang Y M. Conflicting evidence combination of interval-valued belief structures[J]. Systems Engineering-Theory & Practice, 2014, 34(1):256-261.

基金

国家自然科学基金(71533001);教育部人文社会科学研究青年基金(17YJC630014);辽宁省社科规划基金(L13DGL061);中央高校基本科研业务费资助项目(DUT18JC01)
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