A review of population-based metaheuristics for large-scale black-box global optimization—Part I

MN Omidvar, X Li, X Yao - IEEE Transactions on Evolutionary …, 2021 - ieeexplore.ieee.org
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 …

Metaheuristics in large-scale global continues optimization: A survey

S Mahdavi, ME Shiri, S Rahnamayan - Information Sciences, 2015 - Elsevier
Metaheuristic algorithms are extensively recognized as effective approaches for solving high-
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 …

Bio-inspired computation: Where we stand and what's next

J Del Ser, E Osaba, D Molina, XS Yang… - Swarm and Evolutionary …, 2019 - Elsevier
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 …

QANA: Quantum-based avian navigation optimizer algorithm

H Zamani, MH Nadimi-Shahraki… - Engineering Applications of …, 2021 - Elsevier
Differential evolution is an effective and practical approach that is widely applied for solving
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 …

DG2: A faster and more accurate differential grou** for large-scale black-box optimization

MN Omidvar, M Yang, Y Mei, X Li… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
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 …

A level-based learning swarm optimizer for large-scale optimization

Q Yang, WN Chen, J Da Deng, Y Li… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
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 …

[HTML][HTML] Large-scale evolutionary optimization: A review and comparative study

J Liu, R Sarker, S Elsayed, D Essam… - Swarm and Evolutionary …, 2024 - Elsevier
Large-scale global optimization (LSGO) problems have widely appeared in various real-
world applications. However, their inherent complexity, coupled with the curse of …

Gene targeting differential evolution: A simple and efficient method for large-scale optimization

ZJ Wang, JR Jian, ZH Zhan, Y Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Large-scale optimization problems (LSOPs) are challenging because the algorithm is
difficult in balancing too many dimensions and in esca** from trapped bottleneck …