ESO: An enhanced snake optimizer for real-world engineering problems

L Yao, P Yuan, CY Tsai, T Zhang, Y Lu… - Expert Systems with …, 2023 - Elsevier
Meta-heuristic algorithms are an essential way to solve realistic optimization problems.
Developing effective, accurate, and stable meta-heuristic algorithms has become the goal of …

[HTML][HTML] Improved bald eagle search algorithm for global optimization and feature selection

A Chhabra, AG Hussien, FA Hashim - Alexandria Engineering Journal, 2023 - Elsevier
The use of metaheuristics is one of the most encouraging methodologies for taking care of
real-life problems. Bald eagle search (BES) algorithm is the latest swarm-intelligence …

[HTML][HTML] Stochastic optimal power flow analysis of power system with renewable energy sources using Adaptive Lightning Attachment Procedure Optimizer

A Adhikari, F Jurado, S Naetiladdanon… - International Journal of …, 2023 - Elsevier
The integration of several renewable energy sources (RESs), such as photovoltaic
generation (PVG) and wind turbine generation (WTG), introduces a significant amount of …

Combined cubic generalized ball surfaces: Construction and shape optimization using an enhanced JS algorithm

G Hu, M Li, J Zhong - Advances in Engineering Software, 2023 - Elsevier
The construction and shape optimization of complex shape-adjustable surfaces is a crucial
and intractable technique in Computer Aided geometric Design (CAGD), which has a wide …

Enhanced marine predator algorithm for global optimization and engineering design problems

SB Aydemir - Advances in Engineering Software, 2023 - Elsevier
Marine predator algorithm adopts the policy of optimal encounter rate in biological
interaction between predator and prey, inspired by the Lévy and Brownian motions …

A local opposition-learning golden-sine grey wolf optimization algorithm for feature selection in data classification

Z Li - Applied Soft Computing, 2023 - Elsevier
The classification problem is an important research topic in machine learning and data
mining. Feature selection can remove irrelevant and redundant features and improve …

[HTML][HTML] Stochastic optimal power flow analysis of power systems with wind/PV/TCSC using a developed Runge Kutta optimizer

M Ebeed, A Mostafa, MM Aly, F Jurado… - International Journal of …, 2023 - Elsevier
Recently, renewable energy resources such as wind turbines (WTs) and photovoltaic (PV)
systems are wildly installed in electrical systems. However, the main challenge that related …

Chaotic opposition learning with mirror reflection and worst individual disturbance grey wolf optimizer for continuous global numerical optimization

OR Adegboye, AK Feda, OS Ojekemi, EB Agyekum… - Scientific Reports, 2024 - nature.com
The effective meta-heuristic technique known as the grey wolf optimizer (GWO) has shown
its proficiency. However, due to its reliance on the alpha wolf for guiding the position …

[HTML][HTML] A quasi-oppositional learning of updating quantum state and Q-learning based on the dung beetle algorithm for global optimization

Z Wang, L Huang, S Yang, D Li, D He… - Alexandria Engineering …, 2023 - Elsevier
There are many tricky optimization problems in real life, and metaheuristic algorithms are the
most effective way to solve optimization problems at a lower cost. The dung beetle …

Self-learning salp swarm algorithm for global optimization and its application in multi-layer perceptron model training

Z Yang, Y Jiang, WC Yeh - Scientific Reports, 2024 - nature.com
Optimization problems are common across various fields, and one effective solution is the
swarm intelligence algorithm. It is essential for the algorithm to deliver high-quality solutions …