Circulatory System Based Optimization (CSBO): an expert multilevel biologically inspired meta-heuristic algorithm

M Ghasemi, MA Akbari, C Jun, SM Bateni… - Engineering …, 2022 - Taylor & Francis
The optimization problems are becoming more complicated, requiring new and efficient
optimization techniques to solve them. Many bio-inspired meta-heuristic algorithms have …

Review of applications of TLBO algorithm and a tutorial for beginners to solve the unconstrained and constrained optimization problems

R Rao - Decision science letters, 2016 - growingscience.com
The teaching-learning-based optimization (TLBO) algorithm is finding a large number of
applications in different fields of engineering and science since its introduction in 2011. The …

Chaotic RIME optimization algorithm with adaptive mutualism for feature selection problems

M Abdel-Salam, G Hu, E Çelik… - Computers in Biology …, 2024 - Elsevier
The RIME optimization algorithm is a newly developed physics-based optimization algorithm
used for solving optimization problems. The RIME algorithm proved high-performing in …

A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module

K Yu, B Qu, C Yue, S Ge, X Chen, J Liang - Applied energy, 2019 - Elsevier
In order to carry out the evaluation, control and maximum power point tracking on
photovoltaic (PV) systems, accurate and reliable model parameter identification of PV cell …

Optimization of an auto drum fashioned brake using the elite opposition-based learning and chaotic k-best gravitational search strategy based grey wolf optimizer …

Y Yuan, X Mu, X Shao, J Ren, Y Zhao, Z Wang - Applied Soft Computing, 2022 - Elsevier
Highly non-linear optimization problems are widely found in many real-world engineering
applications. To tackle these problems, a novel assisted optimization strategy, named elite …

Parameters identification of photovoltaic models using an improved JAYA optimization algorithm

K Yu, JJ Liang, BY Qu, X Chen, H Wang - Energy Conversion and …, 2017 - Elsevier
Parameters identification of photovoltaic (PV) models based on measured current-voltage
characteristic curves is significant for the simulation, evaluation, and control of PV systems …

Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models

K Yu, JJ Liang, BY Qu, Z Cheng, H Wang - Applied energy, 2018 - Elsevier
Obtaining appropriate parameters of photovoltaic models based on measured current-
voltage data is crucial for the evaluation, control, and optimization of photovoltaic systems …

Lithium-ion battery charging management considering economic costs of electrical energy loss and battery degradation

K Liu, X Hu, Z Yang, Y **e, S Feng - Energy conversion and management, 2019 - Elsevier
Technical challenges facing the development of battery economic charging for energy
management arise from various contradictory objectives, immeasurable internal states, and …

Parameters identification of photovoltaic models using self-adaptive teaching-learning-based optimization

K Yu, X Chen, X Wang, Z Wang - Energy Conversion and Management, 2017 - Elsevier
Parameters identification of photovoltaic (PV) model based on measured current-voltage
characteristic curves plays an important role in the simulation and evaluation of PV systems …

An improved Genghis Khan optimizer based on enhanced solution quality strategy for global optimization and feature selection problems

M Abdel-Salam, AI Alzahrani, F Alblehai… - Knowledge-Based …, 2024 - Elsevier
Feature selection (FS) is the activity of defining the most contributing feature subset among
all used features to improve the superiority of datasets with a large number of dimensions by …