.png){kind=icon}
返回
A multi-objective hyper-heuristic algorithm based on adaptive epsilon-greedy selection
.png){kind=icon}
OA
AI
DOI：10.1007/s40747-020-00230-8.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A variety of meta-heuristics have shown promising performance for solving multi-objective optimization problems (MOPs). However, existing meta-heuristics may have the best performance on particular MOPs, but may not perform well on the other MOPs. To improve the cross-domain ability, this paper presents a multi-objective hyper-heuristic algorithm based on adaptive epsilon-greedy selection (HH_EG) for solving MOPs. To select and combine low-level heuristics (LLHs) during the evolutionary procedure, this paper also proposes an adaptive epsilon-greedy selection strategy. The proposed hyper-heuristic can solve problems from varied domains by simply changing LLHs without redesigning the high-level strategy. Meanwhile, HH_EG does not need to tune parameters, and is easy to be integrated with various performance indicators. We test HH_EG on the classical DTLZ test suite, the IMOP test suite, the many-objective MaF test suite, and a test suite of a real-world multi-objective problem. Experimental results show the effectiveness of HH_EG in combining the advantages of each LLH and solving cross-domain problems.
Keyword:
Hyper-heuristics
Multi-objective optimization
Adaptive epsilon-greedy selection strategy
Cross-domain problems
期刊
IF:
4.6
论文数:
2.1K
被引数:
6.6K
机构
引用论文
Refining Estimates of Bird Collision and Electrocution Mortality at Power Lines in the United States.png)
PLoS ONE
OAAI
PLoS ONEIF0
OAAI分享收藏PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective OptimizationPlatEMO: 用于进化多目标优化的MATLAB平台OAAI
OAAI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Tackling Large-Scale and Combinatorial Bi-Level Problems With a Genetic Programming Hyper-Heuristic用遗传编程超启发式解决大规模和组合双层问题
PREAI
分享收藏分享收藏A Strengthened Dominance Relation Considering Convergence and Diversity for Evolutionary Many-Objective Optimization进化多目标优化中考虑收敛性和多样性的增强优势关系OAAI
OAAI分享收藏The Predictive Validity of the GRE Across Graduate Outcomes: A Meta-Analysis of Trends Over TimeOAAI
OAAI分享收藏
查看更多内容