.png){kind=icon}
返回
Game theory based solution selection for multi-objective redundancy allocation in interval-valued problem parameters
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ress.2020.106932.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper presents a multi-objective redundancy allocation problem (MORAP) for maximizing system reliability and simultaneously minimizing system cost with limitations on system entropy, which is essential for achieving system stability and sustainability. Entropy is an important part of this new model because it provides a measure of randomness, which should be limited to avoid risky solutions. Both component reliability estimates and component cost estimates are considered to formulate the model in more realistic sense. In real-life MORAP, the Pareto optimal set can be extremely large. A selection procedure based on the notion of game theory is then proposed to determine representative solutions for solving the problem. For MORAP, the game theoretical framework can select representative solutions effectively with higher system reliability, lower associated variance of the reliability estimate and higher system entropy. The validity and the performance of the proposed approach are tested through three numerical examples, and computational results are analyzed.
Keyword:
Reliability optimization
Multi-objective optimization
Entropy
Game theory
Interval numbers
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
R
IF:
11
论文数:
9.0K
被引数:
4.2W
机构
引用论文
A new multi-objective particle swarm optimization method for solving reliability redundancy allocation problems一种新的多目标粒子群优化方法求解可靠性冗余分配问题
.png){kind=icon}
PREAI
分享收藏分享收藏Solving the redundancy allocation problem with multiple strategy choices using a new simplified particle swarm optimization使用新的简化粒子群优化算法解决具有多策略选择的冗余分配问题
PREAI
分享收藏
查看更多内容