A review of population-based metaheuristics for large-scale black-box global optimization—Part I
Scalability of optimization algorithms is a major challenge in co** with the ever-growing
size of optimization problems in a wide range of application areas from high-dimensional …
size of optimization problems in a wide range of application areas from high-dimensional …
Metaheuristics in large-scale global continues optimization: A survey
Metaheuristic algorithms are extensively recognized as effective approaches for solving high-
dimensional optimization problems. These algorithms provide effective tools with important …
dimensional optimization problems. These algorithms provide effective tools with important …
SF-FWA: A self-adaptive fast fireworks algorithm for effective large-scale optimization
M Chen, Y Tan - Swarm and Evolutionary Computation, 2023 - Elsevier
Computationally efficient algorithms for large-scale black-box optimization have become
increasingly important in recent years due to the growing complexity of engineering and …
increasingly important in recent years due to the growing complexity of engineering and …
Bio-inspired computation: Where we stand and what's next
In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …
with the mimicking of behavioral patterns and social phenomena observed in nature towards …
QANA: Quantum-based avian navigation optimizer algorithm
Differential evolution is an effective and practical approach that is widely applied for solving
global optimization problems. Nevertheless, its effectiveness and scalability are decreased …
global optimization problems. Nevertheless, its effectiveness and scalability are decreased …
Competitive swarm optimizer with dynamic multi-competitions and convergence accelerator for large-scale optimization problems
C Huang, D Wu, X Zhou, Y Song, H Chen… - Applied Soft Computing, 2024 - Elsevier
Large-scale optimizations (LSOPs) with high dimensional decision variables have become
one of the most challenging problems in engineering optimization. High dimensional …
one of the most challenging problems in engineering optimization. High dimensional …
DG2: A faster and more accurate differential grou** for large-scale black-box optimization
Identification of variable interaction is essential for an efficient implementation of a divide-
and-conquer algorithm for large-scale black-box optimization. In this paper, we propose an …
and-conquer algorithm for large-scale black-box optimization. In this paper, we propose an …
A level-based learning swarm optimizer for large-scale optimization
In pedagogy, teachers usually separate mixed-level students into different levels, treat them
differently and teach them in accordance with their cognitive and learning abilities. Inspired …
differently and teach them in accordance with their cognitive and learning abilities. Inspired …
[HTML][HTML] Large-scale evolutionary optimization: A review and comparative study
Large-scale global optimization (LSGO) problems have widely appeared in various real-
world applications. However, their inherent complexity, coupled with the curse of …
world applications. However, their inherent complexity, coupled with the curse of …
Gene targeting differential evolution: A simple and efficient method for large-scale optimization
Large-scale optimization problems (LSOPs) are challenging because the algorithm is
difficult in balancing too many dimensions and in esca** from trapped bottleneck …
difficult in balancing too many dimensions and in esca** from trapped bottleneck …