Risk decision-making method using interval numbers and its application based on the prospect value with multiple reference points

加权 排名(信息检索) 计算机科学 动态决策 前景理论 区间(图论) 集合(抽象数据类型) 过程(计算) 数学优化 加权和模型 选择(遗传算法) 理想(伦理) 运筹学 最优决策 数学 数据挖掘 人工智能 决策树 组合数学 医学 哲学 财务 认识论 经济 放射科 程序设计语言 操作系统
作者
Jianjun Zhu,Zhenzhen Ma,Hehua Wang,Ye Chen
出处
期刊:Information Sciences [Elsevier BV]
卷期号:385-386: 415-437 被引量:43
标识
DOI:10.1016/j.ins.2017.01.007
摘要

A multi-attribute risk decision-making problem using interval numbers is studied based on the prospect theory. A decision-making process often involves various reference standards resulting from different decision-making mentalities and contexts. To solve these kinds of decision-making problems, we propose a risk decision-making method with multiple reference points for both static and dynamic situations. First, the guidelines for setting reference points under both static and dynamic conditions are provided based on the nature of the decision-making problem. Second, both expected values and positive ideal points for alternatives are set for the static decision-making strategy, and three reference points are provided for the dynamic strategy, including expected values, positive ideal points, and the development status of alternatives according to the guidelines. Third, characterization techniques used to solve prospect values of decision-making alternatives are proposed for both static and dynamic decision-making problems. Then, a detailed analysis is provided in terms of weighting functions and prospect values. In addition, two optimization models using the attribute weight and multi-stage weight are established by considering the sensitivity of these two weights to the decision-making problem, with the aim of maximizing the differentiation degree of alternatives. On that basis, a ranking analysis is provided for the alternatives. Finally, the proposed method is applied to two cases, including supplier selection of key components for large aircraft and an emergency event, to illustrate the application and feasibility of the method.
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