A comprehensive review of krill herd algorithm: variants, hybrids and applications
Krill herd (KH) is a novel swarm-based metaheuristic optimization algorithm inspired by the
krill herding behavior. The objective function in the KH optimization process is based on the …
krill herding behavior. The objective function in the KH optimization process is based on the …
A comprehensive review: Krill Herd algorithm (KH) and its applications
Krill Herd (KH) algorithm is a class of nature-inspired algorithm, which simulates the herding
behavior of krill individuals. It has been successfully utilized to tackle many optimization …
behavior of krill individuals. It has been successfully utilized to tackle many optimization …
A novel meta-heuristic algorithm for solving numerical optimization problems: Ali Baba and the forty thieves
This paper presents a novel meta-heuristic algorithm called Ali Baba and the forty thieves
(AFT) for solving global optimization problems. Recall the famous tale of Ali Baba and the …
(AFT) for solving global optimization problems. Recall the famous tale of Ali Baba and the …
Chaotic vortex search algorithm: metaheuristic algorithm for feature selection
Abstract The Vortex Search Algorithm (VSA) is a meta-heuristic algorithm that has been
inspired by the vortex phenomenon proposed by Dogan and Olmez in 2015. Like other meta …
inspired by the vortex phenomenon proposed by Dogan and Olmez in 2015. Like other meta …
Optimal tuning of fractional order PID controller for DC motor speed control via chaotic atom search optimization algorithm
B Hekimoğlu - IEEE access, 2019 - ieeexplore.ieee.org
In this paper, atom search optimization (ASO) algorithm and a novel chaotic version of it
[chaotic ASO (ChASO)] are proposed to determine the optimal parameters of the fractional …
[chaotic ASO (ChASO)] are proposed to determine the optimal parameters of the fractional …
Optimal allocation of electric vehicle charging stations and renewable distributed generation with battery energy storage in radial distribution system considering time …
K Balu, V Mukherjee - Journal of Energy Storage, 2023 - Elsevier
The addition of electric vehicle (EV) charging station (EVCS)/EV battery swapping stations
(EVBSSs) in radial distribution system (RDS) draws extra real power from the distribution …
(EVBSSs) in radial distribution system (RDS) draws extra real power from the distribution …
Evolutionary population dynamics and grey wolf optimizer
S Saremi, SZ Mirjalili, SM Mirjalili - Neural Computing and Applications, 2015 - Springer
Evolutionary population dynamics (EPD) deal with the removal of poor individuals in nature.
It has been proven that this operator is able to improve the median fitness of the whole …
It has been proven that this operator is able to improve the median fitness of the whole …
Chaotic gravitational constants for the gravitational search algorithm
S Mirjalili, AH Gandomi - Applied soft computing, 2017 - Elsevier
In a population-based meta-heuristic, the search process is divided into two main phases:
exploration versus exploitation. In the exploration phase, a random behavior is fruitful to …
exploration versus exploitation. In the exploration phase, a random behavior is fruitful to …
Let a biogeography-based optimizer train your multi-layer perceptron
Abstract The Multi-Layer Perceptron (MLP), as one of the most-widely used Neural Networks
(NNs), has been applied to many practical problems. The MLP requires training on specific …
(NNs), has been applied to many practical problems. The MLP requires training on specific …
Biogeography-based optimisation with chaos
S Saremi, S Mirjalili, A Lewis - Neural Computing and Applications, 2014 - Springer
The biogeography-based optimisation (BBO) algorithm is a novel evolutionary algorithm
inspired by biogeography. Similarly, to other evolutionary algorithms, entrapment in local …
inspired by biogeography. Similarly, to other evolutionary algorithms, entrapment in local …