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 …
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 coping 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 …
A recursive decomposition method for large scale continuous optimization
Cooperative co-evolution (CC) is an evolutionary computation framework that can be used
to solve high-dimensional optimization problems via a “divide-and-conquer” mechanism …
to solve high-dimensional optimization problems via a “divide-and-conquer” mechanism …
A review of population-based metaheuristics for large-scale black-box global optimization—Part II
MN Omidvar, X Li, X Yao - IEEE Transactions on Evolutionary …, 2021 - ieeexplore.ieee.org
This article is the second part of a two-part survey series on large-scale global optimization.
The first part covered two major algorithmic approaches to large-scale optimization, namely …
The first part covered two major algorithmic approaches to large-scale optimization, namely …
Decomposition for large-scale optimization problems with overlapping components
In this paper we use a divide-and-conquer approach to tackle large-scale optimization
problems with overlapping components. Decomposition for an overlapping problem is …
problems with overlapping components. Decomposition for an overlapping problem is …
[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 …
[HTML][HTML] Systematic review of the life cycle optimization literature, and recommendations for performance of life cycle optimization studies
Life cycle optimization (LCO) refers to the integration of objectives calculated using a life-
cycle based framework into mathematical optimization problems. Application of LCO may …
cycle based framework into mathematical optimization problems. Application of LCO may …
Adaptive threshold parameter estimation with recursive differential grouping for problem decomposition
Problem decomposition plays an essential role in the success of cooperative co-evolution
(CC), when used for solving large-scale optimization problems. The recently proposed …
(CC), when used for solving large-scale optimization problems. The recently proposed …
Cooperative coevolutionary differential evolution with linkage measurement minimization for large-scale optimization problems in noisy environments
Many optimization problems suffer from noise, and the noise combined with the large-scale
attributes makes the problem complexity explode. Cooperative coevolution (CC) based on …
attributes makes the problem complexity explode. Cooperative coevolution (CC) based on …
[PDF][PDF] An improved spotted hyena optimizer for PID parameters in an AVR system
G Zhou, J Li, Z Tang, Q Luo, Y Zhou - Math. Biosci. Eng, 2020 - aimspress.com
In this paper, an improved spotted hyena optimizer (ISHO) with a nonlinear convergence
factor is proposed for proportional integral derivative (PID) parameter optimization in an …
factor is proposed for proportional integral derivative (PID) parameter optimization in an …