摘要
多粒度群决策是从决策信息中的多粒度特征出发,利用粒计算模型对群决策问题进行高效建模与分析的过程.现有多数多粒度群决策方法仅可提供单一的决策结果,然而不同方法带来的决策结果往往存在差异.为了深入探索犹豫模糊语言信息系统中的稳健型多粒度群决策方法,依据多粒度概率粗糙集、MULTIMOORA(Multi-Objective Optimization by Ratio Analysis Plus the Full Multi-plicative Form)和TPOP(Technique of Precise Order Preference)建立一种面向多粒度群决策的新型犹豫模糊语言多粒度计算方法.首先结合犹豫模糊语言术语集与多粒度概率粗糙集,提出犹豫模糊语言多粒度概率粗糙集模型,然后依据离差最大化法计算属性权重与决策者权重,并结合TPOP建立犹豫模糊语言稳健型多粒度群决策方法.最后,通过医学实例验证提出方法的可行性与有效性.
From the aspect of multi-granularity features existed in decision-making information,multi-granularity group decision-making acts as a process of efficient modeling and analysis for group decision-making problems via granular computing models.Most of existing multi-granularity group decision-making methods only provide single decision results,however,diverse methods usually lead to diverse decision results.For the sake of deeply exploring robust multi-granularity group decision-making methods in hesitant fuzzy linguistic information systems,this paper investigates a brand-new hesitant fuzzy linguistic multi-granularity calculation method in light of multigranulation probabilistic rough sets,MULTIMOORA(Multi-Objective Optimization by Ratio Analysis Plus the Full Multi-plicative Form)and TPOP(Technique of Precise Order Preference)for multi-granularity group decision-making.First,by combining hesitant fuzzy linguistic term sets with multigranulation probabilistic rough sets,this paper puts forward hesitant fuzzy linguistic multigranulation probabilistic rough set models.Second,the weight of attributes and decision-makers are calculated based on the maximum deviation method,and a hesitant fuzzy linguistic robust multi-granularity group decision-making method is constructed in light of the TPOP method.Finally,the feasibility and effectiveness of the presented method are verified by a medical case analysis.
作者
李小川
张超
李德玉
上官学奎
马瑾男
陆文瑞
Li Xiaochuan;Zhang Chao;Li Deyu;Shangguan Xuekui;Ma Jinnan;Lu Wenrui(School of Computer and Information Technology,Shanxi University,Taiyuan,030006,China;Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education,Shanxi University,Taiyuan,030006,China;Shanxi Information Industry Technology Research Institute Co.,Ltd.,Taiyuan,030012,China)
出处
《南京大学学报（自然科学版）》
CAS
CSCD
北大核心
2023年第1期22-34,共13页
Journal of Nanjing University（Natural Science）
基金
国家自然科学基金(62272284,61806116,62072294,61972238)
山西省数字经济发展研究(202104031402023)
信息技术应用创新省技术创新中心(202104010911033)
山西省科技创新青年人才团队项目(202204051001015)
山西省重点研发计划(国际科技合作)(201903D421041)
山西省筹资金资助回国留学人员科研项目(2022-007)
山西省研究生教育教学改革课题(2021YJJG041)
小店区-山西大学产学研合作项目(202003S08)
山西省高等学校青年科研人员培育计划
山西省高等学校优秀成果培育项目(2019SK036)
山西大学研究生教育创新项目。
