Recent advances in harris hawks optimization: A comparative study and applications
The Harris hawk optimizer is a recent population-based metaheuristics algorithm that
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …
A new chaotic Lévy flight distribution optimization algorithm for solving constrained engineering problems
This work proposed a new metaheuristic dubbed as Chaotic Lévy flight distribution (CLFD)
algorithm, to address physical world engineering optimization problems that incorporate the …
algorithm, to address physical world engineering optimization problems that incorporate the …
A novel chaotic Runge Kutta optimization algorithm for solving constrained engineering problems
This study proposes a novel hybrid metaheuristic optimization algorithm named chaotic
Runge Kutta optimization (CRUN). In this study, 10 diverse chaotic maps are being …
Runge Kutta optimization (CRUN). In this study, 10 diverse chaotic maps are being …
Hunger games search algorithm for global optimization of engineering design problems
The modernization in automobile industries has been booming in recent times, which has
led to the development of lightweight and fuel-efficient design of different automobile …
led to the development of lightweight and fuel-efficient design of different automobile …
A high-precision and transparent step-wise diagnostic framework for hot-rolled strip crown
C Ding, J Sun, X Li, W Peng, D Zhang - Journal of Manufacturing Systems, 2023 - Elsevier
The strip crown plays a crucial role in determining the quality of products in strip hot rolling.
Machine learning (ML) methods have shown promise in crown prediction by effectively …
Machine learning (ML) methods have shown promise in crown prediction by effectively …
A novel hybrid flow direction optimizer-dynamic oppositional based learning algorithm for solving complex constrained mechanical design problems
In this present work, mechanical engineering optimization problems are solved by
employing a novel optimizer (HFDO-DOBL) based on a physics-based flow direction …
employing a novel optimizer (HFDO-DOBL) based on a physics-based flow direction …
A novel generalized normal distribution optimizer with elite oppositional based learning for optimization of mechanical engineering problems
Optimization of engineering discipline problems are quite a challenging task as they carry
design parameters and various constraints. Metaheuristic algorithms can able to handle …
design parameters and various constraints. Metaheuristic algorithms can able to handle …
NLBBODE optimizer for accurate and fast modeling of photovoltaic module/string generator and its application to solve real-world constrained optimization problems
In this paper, a new optimizer is presented to quickly and accurately identify parameters of
the photovoltaic (PV) module/string models. This optimizer is named Nested Loop …
the photovoltaic (PV) module/string models. This optimizer is named Nested Loop …
Enhancing the performance of Piezoelectric Energy Harvester under electrostatic actuation using a robust metaheuristic algorithm
This study proposes a novel shape optimization methodology based on evolutionary
algorithms to maximize the harvesting energy from piezoelectric energy harvester stimulated …
algorithms to maximize the harvesting energy from piezoelectric energy harvester stimulated …
A novel hybrid Fick's law algorithm-quasi oppositional–based learning algorithm for solving constrained mechanical design problems
In this article, a recently developed physics-based Fick's law optimization algorithm is
utilized to solve engineering optimization challenges. The performance of the algorithm is …
utilized to solve engineering optimization challenges. The performance of the algorithm is …