摘要
以突发危机事件应急决策为应用背景,讨论了双论域上模糊粗糙集的基本理论,建立了基于模糊相容关系的双论域模糊粗糙集模型.在此基础上,把突发危机事件应急决策转化为一个具有模糊决策对象的双论域决策近似空间上的粗糙近似问题,构建了基于双论域模糊粗糙集的应急决策模型.首先在双论域近似空间中计算模糊决策对象的上(下)近似,进而结合经典非确定型决策的思想给出了突发危机事件应急决策的规则.同时,给出了模型的算法.该模型给出了一种在不完全信息环境下应急决策的方法,给出了在充分考虑决策者个人偏好信息基础上的决策置信度以及最优决策规则.该方法能够比较充分地符合应急决策信息不充分、资源有限以及时间紧迫的基本特征,进而对突发危机事件应急决策提供科学的理论基础和现实的决策方法.最后,通过应用算例说明了模型的应用过程,结果验证了本文给出模型的有效性。
In this paper,we discuss the theory of fuzzy rough set over two universes with the background of emergency decision-making. Then we define a fuzzy rough set model based on fuzzy compatible relation over two universes. By the theory of fuzzy rough set over two universes,the emergency decision-making changes into a rough approximation of a fuzzy decision object on the decision approximation space over two universes. So,we construct the model of emergency decision making based on fuzzy rough set over two universes. We first compute the lower（ upper） approximation of the fuzzy decision object with respect to the approximation space over two universes, and then present the decision rules by combing the idea of uncertainty decision-making. Moreover,the algorithm of the model is given. This model gives a kind of decision approach to emergency decision-making under the condition of incomplete information. Furthermore,it also gives the optimal decision rules with the confidence coefficient by considering the preference of the decision-makers. The proposed method could give a properly descriptive of the characters for the emergency decision making with incomplete information,limited recourses of humans and materials and urgently time. Therefore,it can provide a basic theory and a decision approach in practice for emergency decision-making. Finally,the validity of the approach and the applied process is tested by a numerical example.
出处
《运筹与管理》
CSSCI
CSCD
北大核心
2014年第2期41-48,共8页
Operations Research and Management Science
基金
国家自然科学基金资助项目(71161016,71071113)
甘肃省自然科学基金资助项目(1308RJYA020)
中央高校基本科研业务费专项资金
关键词
应急决策
模糊粗糙集
双论域
非确定型决策
emergency decision-making
fuzzy rough set
two universes
uncertainty decision-making
