.png){kind=icon}
返回
A Multiscenario Optimization Evolutionary Algorithm Based on Transfer Framework
.png){kind=icon}
PRE
AI
DOI：10.1109/TEVC.2022.3211643.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Multiscenario optimization problems involve multiple scenarios to be optimized simultaneously, where each scenario corresponds to a multiobjective optimization problem with specific operating conditions. The goal is to find a group of public compromised optimal solutions (PCOSs) achieving compromised optimal in every scenario. This type of optimization problems widely exists in real-world applications, but the research on it is few. In this article, a Multiscenario Optimization Evolutionary Algorithm based on a transfer framework is proposed. In one iteration, for each scenario, its knee solutions are recognized as its transfer candidates and are used to construct a constraint hyperplane, which determines whether transfer candidates from other scenarios can be the transferable solutions in this underlying scenario. Then, among all transfer candidates, those accepted by all scenarios are identified as the PCOSs and stored in archive. Afterwards, the archive updating process is applied to guarantee the optimality of solutions in archive and control the size of archive. Finally, each scenario's accepted transferable solutions are utilized in its offspring generation, thus achieving information transfer between different scenarios. Experimental results on a group of benchmark functions verify the superiority of the proposed design in terms of both optimality and computational efficiency over existing approaches.
Keyword:
Optimization
Task analysis
Evolutionary computation
Statistics
Sociology
Uncertainty
Tropical cyclones
Knowledge transfer
multiobjective evolutionary algorithm (MOEA)
multiscenario optimization problem (MSOP)
期刊
IF:
12
论文数:
1.9K
被引数:
2.4W
机构
引用论文
Effects of Group Counseling Transmitted Through Videoconferencing on Changes in Eating Behaviors
.png){kind=icon}
PREAI
分享收藏Multiobjective evolutionary algorithms: A comparative case study and the Strength Pareto approach多目标进化算法: 比较案例研究和强度帕累托方法
PREAI
分享收藏分享收藏An Effective Knowledge Transfer Approach for Multiobjective Multitasking Optimization多目标多任务优化的有效知识转移方法
PREAI
分享收藏Effect of sintering temperature on mechanical and thermophysical properties of biowaste-added fired clay bricks烧结温度对添加生物废料的烧结粘土砖的力学和热物理性能的影响
PREAI
分享收藏分享收藏A Meta-Knowledge Transfer-Based Differential Evolution for Multitask Optimization基于元知识转移的差分进化多任务优化算法
OAAI
OAAI分享收藏
查看更多内容