An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges
As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …
Metaheuristics: a comprehensive overview and classification along with bibliometric analysis
Research in metaheuristics for global optimization problems are currently experiencing an
overload of wide range of available metaheuristic-based solution approaches. Since the …
overload of wide range of available metaheuristic-based solution approaches. Since the …
Comprehensive taxonomies of nature-and bio-inspired optimization: Inspiration versus algorithmic behavior, critical analysis recommendations
In recent algorithmic family simulates different biological processes observed in Nature in
order to efficiently address complex optimization problems. In the last years the number of …
order to efficiently address complex optimization problems. In the last years the number of …
Biped robot stability based on an A–C parametric whale optimization algorithm
The easy gait stability of biped robot is an important issue and has been mentioned in
different works in literature. To evaluate the walking stability, we performed zero moment …
different works in literature. To evaluate the walking stability, we performed zero moment …
Optimal power flow in direct-current power grids via black hole optimization
OS Velasquez, OD Montoya, VM Garrido Arevalo… - 2019 - repositorio.utb.edu.co
This paper addresses the Optimal Power Flow (OPF) problem in DC power microgrids via a
combinatorial optimization technique known as Black Hole Optimization (BHO). Such …
combinatorial optimization technique known as Black Hole Optimization (BHO). Such …
A hybrid biogeography-based optimization algorithm to solve high-dimensional optimization problems and real-world engineering problems
Z Zhang, Y Gao, Y Liu, W Zuo - Applied Soft Computing, 2023 - Elsevier
According to our extensive investigation, Biogeography-based optimization (BBO) and its
variants have not been applied to solve high-dimensional optimization problems. To make a …
variants have not been applied to solve high-dimensional optimization problems. To make a …
Evaluation of bayesian network structure learning using elephant swarm water search algorithm
Bayesian networks are useful analytical models for designing the structure of knowledge in
machine learning which can represent probabilistic dependency relationships among the …
machine learning which can represent probabilistic dependency relationships among the …
An in-depth and contrasting survey of meta-heuristic approaches with classical feature selection techniques specific to cervical cancer
S Kurman, S Kisan - Knowledge and Information Systems, 2023 - Springer
Data mining and machine learning algorithms' performance is degraded by data of high-
dimensional nature due to an issue called “curse of dimensionality”. Feature selection is a …
dimensional nature due to an issue called “curse of dimensionality”. Feature selection is a …
Structure learning of Bayesian networks using elephant swarm water search algorithm
Bayesian networks are useful analytical models for designing the structure of knowledge in
machine learning. Bayesian networks can represent probabilistic dependency relationships …
machine learning. Bayesian networks can represent probabilistic dependency relationships …
Modeling of photovoltaic systems using modified elephant swarm water search algorithm
S Mandal - International Journal of Modelling and Simulation, 2020 - Taylor & Francis
ABSTRACT A highly accurate modeling of photovoltaic (PV) systems from experimental data
is a very important task for electronic engineers for efficient design of PV systems. Suitable …
is a very important task for electronic engineers for efficient design of PV systems. Suitable …