Recent advances in differential evolution–an updated survey
Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary
optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed …
optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed …
Metaheuristics for solving global and engineering optimization problems: review, applications, open issues and challenges
EH Houssein, MK Saeed, G Hu… - Archives of Computational …, 2024 - Springer
The greatest and fastest advances in the computing world today require researchers to
develop new problem-solving techniques capable of providing an optimal global solution …
develop new problem-solving techniques capable of providing an optimal global solution …
An insight into bio-inspired and evolutionary algorithms for global optimization: review, analysis, and lessons learnt over a decade of competitions
Over the recent years, continuous optimization has significantly evolved to become the
mature research field it is nowadays. Through this process, evolutionary algorithms had an …
mature research field it is nowadays. Through this process, evolutionary algorithms had an …
A review of the recent use of Differential Evolution for Large-Scale Global Optimization: An analysis of selected algorithms on the CEC 2013 LSGO benchmark suite
This paper gives a review of recent extensions of the Differential Evolution (DE) algorithm for
use in Large-Scale Global Optimization (LSGO) and presents an empirical analysis of DE …
use in Large-Scale Global Optimization (LSGO) and presents an empirical analysis of DE …
A multi-population differential evolution with best-random mutation strategy for large-scale global optimization
Y Ma, Y Bai - Applied Intelligence, 2020 - Springer
Differential evolution (DE) is an efficient population-based search algorithm with good
robustness, but it faces challenges in dealing with Large-Scale Global Optimization (LSGO) …
robustness, but it faces challenges in dealing with Large-Scale Global Optimization (LSGO) …
Dynamical Sphere Regrou** Particle Swarm Optimization: A Proposed Algorithm for Dealing with PSO Premature Convergence in Large-Scale Global Optimization
Optimizing large-scale numerical problems is a significant challenge with numerous real-
world applications. The optimization process is complex due to the multi-dimensional search …
world applications. The optimization process is complex due to the multi-dimensional search …
A review of evolutionary algorithms in solving large scale benchmark optimisation problems
P Mohapatra, S Roy, KN Das… - … of Mathematics in …, 2022 - inderscienceonline.com
Optimisation problems containing huge total of decision variables are termed as large scale
global optimisation problems which are often considered as abundant challenges to the …
global optimisation problems which are often considered as abundant challenges to the …
[HTML][HTML] On improving adaptive problem decomposition using differential evolution for large-scale optimization problems
Modern computational mathematics and informatics for Digital Environments deal with the
high dimensionality when designing and optimizing models for various real-world …
high dimensionality when designing and optimizing models for various real-world …
Investigation of improved cooperative coevolution for large-scale global optimization problems
Modern real-valued optimization problems are complex and high-dimensional, and they are
known as “large-scale global optimization (LSGO)” problems. Classic evolutionary …
known as “large-scale global optimization (LSGO)” problems. Classic evolutionary …
A novel local search method for LSGO with golden ratio and dynamic search step
Depending on the develo** technology, large-scale problems have emerged in many
areas such as business, science, and engineering. Therefore, large-scale optimization …
areas such as business, science, and engineering. Therefore, large-scale optimization …