Opposition based learning: A literature review

S Mahdavi, S Rahnamayan, K Deb - Swarm and evolutionary computation, 2018‏ - Elsevier
Opposition-based Learning (OBL) is a new concept in machine learning, inspired from the
opposite relationship among entities. In 2005, for the first time the concept of opposition was …

Review on parameter estimation techniques of solar photovoltaic systems

R Venkateswari, N Rajasekar - International Transactions on …, 2021‏ - Wiley Online Library
Beyond meeting power demand, switching to solar energy especially solar photovoltaic (PV)
offers many advantages like modularity, minimal maintenance, pollution free, and zero …

A survey on new generation metaheuristic algorithms

T Dokeroglu, E Sevinc, T Kucukyilmaz… - Computers & Industrial …, 2019‏ - Elsevier
Metaheuristics are an impressive area of research with extremely important improvements in
the solution of intractable optimization problems. Major advances have been made since the …

An improved moth flame optimization algorithm based on modified dynamic opposite learning strategy

SK Sahoo, AK Saha, S Nama, M Masdari - Artificial Intelligence Review, 2023‏ - Springer
Moth flame optimization (MFO) algorithm is a relatively new nature-inspired optimization
algorithm based on the moth's movement towards the moon. Premature convergence and …

Greedy opposition-based learning for chimp optimization algorithm

M Khishe - Artificial Intelligence Review, 2023‏ - Springer
The chimp optimization algorithm (ChOA) is a hunting-based model and can be utilized as a
set of optimization rules to tackle optimization problems. Although ChOA has shown …

Lens imaging opposition-based learning for differential evolution with cauchy perturbation

F Yu, J Guan, H Wu, Y Chen, X **a - Applied Soft Computing, 2024‏ - Elsevier
Opposition-based learning (OBL) is an effective optimization strategy that enhances the
performance of various global optimization algorithms. Among these algorithms, differential …

Evolving chimp optimization algorithm by weighted opposition-based technique and greedy search for multimodal engineering problems

Q Bo, W Cheng, M Khishe - Applied Soft Computing, 2023‏ - Elsevier
This paper presents an evolved chimp optimization algorithm (ChOA) that uses greedy
search (GS) and opposition-based learning (OBL) to respectively increase the ChOA's …

A multi-strategy enhanced sine cosine algorithm for global optimization and constrained practical engineering problems

H Chen, M Wang, X Zhao - Applied Mathematics and Computation, 2020‏ - Elsevier
Abstract The Sine Cosine Algorithm (SCA) has received much attention from engineering
and scientific fields since it was proposed. Nevertheless, when solving multimodal or …

Adaptive chaotic dynamic learning-based gazelle optimization algorithm for feature selection problems

M Abdel-Salam, H Askr, AE Hassanien - Expert Systems with Applications, 2024‏ - Elsevier
Feature Selection (FS) is considered a crucial procedure for eliminating unnecessary
features from datasets. FS is considered a challenging problem that is difficult to solve …

Biogeography-based optimization

D Simon - IEEE transactions on evolutionary computation, 2008‏ - ieeexplore.ieee.org
Biogeography is the study of the geographical distribution of biological organisms.
Mathematical equations that govern the distribution of organisms were first discovered and …