计算机工程与应用Issue(8)：27-31,5.DOI:10.3778/j.issn.1002-8331.1409-0213
区间值模糊随机多准则决策方法
Methods of interval-valued fuzzy-stochastic multiple-criterion decision-making problem
摘要
Abstract
To solve the interval-valued fuzzy-stochastic multiple-criterion decision-making problems with incomplete infor-mation, two methods are suggested. In the first method, a linear programming model with interval parameters is constructed based on maximal deviations. The optimal weight vector, decision-making matrix consisting of integrated interval values in the states, and decision-making matrix consisting of expected interval values are successively worked out by the opera-tion rules of interval numbers and the located programming model. According to the risk preference level of decision-makers, the expected integrated values of alternatives are gotten. In the second method, the decision matrices with interval-valued fuzzy numbers are transformed into the decision matrices with intuitionistic fuzzy numbers. According to the incomplete criterion weights and programming model, the evaluation intervals of the weighted score functions and the weighted accu-racy functions of the alternatives are worked out under the states. The expected evaluation intervals of the score functions and the accuracy functions of the alternatives are gotten through the incomplete state probabilities. With the help of the risk preference levels, the expected integrated evaluations of the score functions and the accuracy functions of the alterna-tives are attained. In the methods, the rank order of the alternatives comes out in the end. A numeric example shows the validity and the feasibility of the methods.关键词
区间值模糊随机多准则决策/不完全信息/区间数/记分函数/精确函数Key words
interval-valued fuzzy-stochastic multiple-criterion decision-making/incomplete information/interval number/score function/accuracy function分类
管理科学引用本文复制引用
任剑..区间值模糊随机多准则决策方法[J].计算机工程与应用,2015,(8):27-31,5.基金项目
教育部人文社会科学研究青年基金（No.13YJCZH145）；中国博士后科学基金（No.2013M531784）；湖南省哲学社会科学基金（No.12YBA195，No.11YBA232，No.09YBA072）；湖南省科技计划专项项目（No.2014FJ6075）；国家社会科学基金（No.12BJY055）。 （）
