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 …
A survey on evolutionary computation for complex continuous optimization
Complex continuous optimization problems widely exist nowadays due to the fast
development of the economy and society. Moreover, the technologies like Internet of things …
development of the economy and society. Moreover, the technologies like Internet of things …
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 …
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 …
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 …
Cooperative co-evolution with differential grou** for large scale optimization
Cooperative co-evolution has been introduced into evolutionary algorithms with the aim of
solving increasingly complex optimization problems through a divide-and-conquer …
solving increasingly complex optimization problems through a divide-and-conquer …
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 …
Adaptive granularity learning distributed particle swarm optimization for large-scale optimization
Large-scale optimization has become a significant and challenging research topic in the
evolutionary computation (EC) community. Although many improved EC algorithms have …
evolutionary computation (EC) community. Although many improved EC algorithms have …
[PDF][PDF] Benchmark functions for the CEC 2013 special session and competition on large-scale global optimization
This report proposes 15 large-scale benchmark problems as an extension to the existing
CEC'2010 large-scale global optimization benchmark suite. The aim is to better represent a …
CEC'2010 large-scale global optimization benchmark suite. The aim is to better represent a …