Advances in manta ray foraging optimization: A comprehensive survey
This paper comprehensively analyzes the Manta Ray Foraging Optimization (MRFO)
algorithm and its integration into diverse academic fields. Introduced in 2020, the MRFO …
algorithm and its integration into diverse academic fields. Introduced in 2020, the MRFO …
An effective control design approach based on novel enhanced aquila optimizer for automatic voltage regulator
This paper presents a new metaheuristic algorithm by enhancing one of the recently
proposed optimizers named Aquila optimizer (AO). The enhanced AO (enAO) algorithm is …
proposed optimizers named Aquila optimizer (AO). The enhanced AO (enAO) algorithm is …
An intelligent tuning scheme with a master/slave approach for efficient control of the automatic voltage regulator
A new master/slave model driven, and an optimization algorithm-based proportional–
integral–derivative (PID) plus second-order derivative (PIDD2) controller is proposed in this …
integral–derivative (PID) plus second-order derivative (PIDD2) controller is proposed in this …
[HTML][HTML] A review of classical methods and Nature-Inspired Algorithms (NIAs) for optimization problems
PK Mandal - Results in Control and Optimization, 2023 - Elsevier
Optimization techniques are among the most promising methods to deal with real-world
problems, consisting of several objective functions and constraints. Over the decades, many …
problems, consisting of several objective functions and constraints. Over the decades, many …
An enhanced manta ray foraging optimization algorithm for shape optimization of complex CCG-Ball curves
G Hu, M Li, X Wang, G Wei, CT Chang - Knowledge-Based Systems, 2022 - Elsevier
The shape optimization of complex curves is a crucial and intractable technique in computer
aided geometric design and widely used in many product design and manufacturing fields …
aided geometric design and widely used in many product design and manufacturing fields …
Manta ray foraging optimization based on mechanics game and progressive learning for multiple optimization problems
Metaheuristic algorithms are currently being studied in depth by many scholars, and it is an
important task to improve the learning and adaptive capabilities of the algorithms so that …
important task to improve the learning and adaptive capabilities of the algorithms so that …
The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction
This paper focuses on the development of a robust accurate streamflow prediction model by
balancing the abilities of exploitation and exploration to find the best parameters of a …
balancing the abilities of exploitation and exploration to find the best parameters of a …
Optimal PID plus second-order derivative controller design for AVR system using a modified Runge Kutta optimizer and Bode's ideal reference model
This paper presents the development of a new metaheuristic algorithm by modifying one of
the recently proposed optimizers named Runge Kutta optimizer (RUN). The modified RUN …
the recently proposed optimizers named Runge Kutta optimizer (RUN). The modified RUN …
Design and robustness analysis of an Automatic Voltage Regulator system controller by using Equilibrium Optimizer algorithm
In this paper, a novel design method for the determination of the optimal values of the
Proportional–Integral–Derivative (PID) controller parameters of an Automatic Voltage …
Proportional–Integral–Derivative (PID) controller parameters of an Automatic Voltage …
Improved Lévy flight distribution algorithm with FDB-based guiding mechanism for AVR system optimal design
This paper presents the improved version of the Lévy Flight Distribution (LFD) algorithm for
solving real-valued numerical optimization problems. In the proposed algorithm, the Fitness …
solving real-valued numerical optimization problems. In the proposed algorithm, the Fitness …