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 …
Memetic algorithms and memetic computing optimization: A literature review
Memetic computing is a subject in computer science which considers complex structures
such as the combination of simple agents and memes, whose evolutionary interactions lead …
such as the combination of simple agents and memes, whose evolutionary interactions lead …
Enhanced whale optimization algorithm for medical feature selection: A COVID-19 case study
The whale optimization algorithm (WOA) is a prominent problem solver which is broadly
applied to solve NP-hard problems such as feature selection. However, it and most of its …
applied to solve NP-hard problems such as feature selection. However, it and most of its …
[HTML][HTML] 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 …
A survey on optimization metaheuristics
I Boussaïd, J Lepagnot, P Siarry - Information sciences, 2013 - Elsevier
Metaheuristics are widely recognized as efficient approaches for many hard optimization
problems. This paper provides a survey of some of the main metaheuristics. It outlines the …
problems. This paper provides a survey of some of the main metaheuristics. It outlines the …
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 …
Differential evolution with ranking-based mutation operators
W Gong, Z Cai - IEEE Transactions on Cybernetics, 2013 - ieeexplore.ieee.org
Differential evolution (DE) has been proven to be one of the most powerful global numerical
optimization algorithms in the evolutionary algorithm family. The core operator of DE is the …
optimization algorithms in the evolutionary algorithm family. The core operator of DE is the …
Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
The performance of most metaheuristic algorithms depends on parameters whose settings
essentially serve as a key function in determining the quality of the solution and the …
essentially serve as a key function in determining the quality of the solution and the …
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 …
Review of differential evolution population size
AP Piotrowski - Swarm and Evolutionary Computation, 2017 - Elsevier
Abstract Population size of Differential Evolution (DE) algorithms is often specified by user
and remains fixed during run. During the first decade since the introduction of DE the …
and remains fixed during run. During the first decade since the introduction of DE the …