.png){kind=icon}
返回
An interactive satisficing approach for multi-objective optimization with uncertain parameters
.png){kind=icon}
PRE
AI
DOI：10.1007/s10845-014-0998-0.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Uncertain variables are used to describe the phenomenon where uncertainty appears in a complex system. For modeling the multi-objective decision-making problems with uncertain parameters, a class of uncertain optimization is suggested for the decision systems in Liu and Chen (2013), which is called the uncertain multi-objective programming. In order to solve the proposed uncertain multi-objective programming, an interactive uncertain satisficing approach involving the decision-maker's flexible demands is proposed in this paper. It makes an improvement in contrast to the noninteractive methods. Finally, a numerical example about the capital budget problem is given to illustrate the effectiveness of the proposed model and the relevant solving approach.
Keyword:
Multi-objective optimization
Multi-objective programming
Uncertain variable
Uncertain programming
Interactive satisficing approach
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.4
论文数:
3.5K
被引数:
1.1W
机构
引用论文
A non dominated ranking Multi Objective Genetic Algorithm and electre method for unequal area facility layout problems不等面积设施布局问题的非支配排序多目标遗传算法和electre方法
PREAI
分享收藏分享收藏
Conformational change and protein–protein interactions of the fusion protein of Semliki Forest virusSemliki森林病毒融合蛋白的构象变化和蛋白-蛋白相互作用.png)
Nature
NatureIF0
PREAI
分享收藏
查看更多内容