4 papers
Unleashing the Potential of Differential Evolution through Individual-Level Strategy Diversity
Chenchen Feng, Minyang Chen, Zhuozhao Li +1
Since Differential Evolution (DE) is sensitive to strategy choice, most existing variants pursue performance through adaptive mechanisms or intricate designs. While these approache…
TensorNEAT: A GPU-accelerated Library for NeuroEvolution of Augmenting Topologies
Lishuang Wang, Mengfei Zhao, Enyu Liu +2
The NeuroEvolution of Augmenting Topologies (NEAT) algorithm has received considerable recognition in the field of neuroevolution. Its effectiveness is derived from initiating with…
GPU-accelerated Evolutionary Many-objective Optimization Using Tensorized NSGA-III
Hao Li, Zhenyu Liang, Ran Cheng
NSGA-III is one of the most widely adopted algorithms for tackling many-objective optimization problems. However, its CPU-based design severely limits scalability and computational…
Bridging Evolutionary Multiobjective Optimization and GPU Acceleration via Tensorization
Zhenyu Liang, Hao Li, Naiwei Yu +2
Evolutionary multiobjective optimization (EMO) has made significant strides over the past two decades. However, as problem scales and complexities increase, traditional EMO algorit…