RUN beyond the metaphor: An efficient optimization algorithm based on Runge Kutta method
The optimization field suffers from the metaphor-based “pseudo-novel” or “fancy” optimizers.
Most of these cliché methods mimic animals' searching trends and possess a small …
Most of these cliché methods mimic animals' searching trends and possess a small …
Hybrid metaheuristics with evolutionary algorithms specializing in intensification and diversification: Overview and progress report
Nowadays, a promising way to obtain hybrid metaheuristics concerns the combination of
several search algorithms with strong specialization in intensification and/or diversification …
several search algorithms with strong specialization in intensification and/or diversification …
Geyser inspired algorithm: a new geological-inspired meta-heuristic for real-parameter and constrained engineering optimization
Over the past years, many efforts have been accomplished to achieve fast and accurate
meta-heuristic algorithms to optimize a variety of real-world problems. This study presents a …
meta-heuristic algorithms to optimize a variety of real-world problems. This study presents a …
Orthogonal learning covariance matrix for defects of grey wolf optimizer: Insights, balance, diversity, and feature selection
J Hu, H Chen, AA Heidari, M Wang, X Zhang… - Knowledge-Based …, 2021 - Elsevier
This research's genesis is in two aspects: first, a guaranteed solution for mitigating the grey
wolf optimizer's (GWO) defect and deficiencies. Second, we provide new open-minding …
wolf optimizer's (GWO) defect and deficiencies. Second, we provide new open-minding …
Towards augmented kernel extreme learning models for bankruptcy prediction: algorithmic behavior and comprehensive analysis
Y Zhang, R Liu, AA Heidari, X Wang, Y Chen, M Wang… - Neurocomputing, 2021 - Elsevier
Bankruptcy prediction is a crucial application in financial fields to aid in accurate decision
making for business enterprises. Many models may stagnate to low-accuracy results due to …
making for business enterprises. Many models may stagnate to low-accuracy results due to …
Optimization based on performance of lungs in body: Lungs performance-based optimization (LPO)
The development of efficient optimization algorithms is crucial across various scientific
disciplines. As the complexity and diversity of optimization problems continue to grow …
disciplines. As the complexity and diversity of optimization problems continue to grow …
SGOA: annealing-behaved grasshopper optimizer for global tasks
An improved grasshopper optimization algorithm (GOA) is proposed in this paper, termed as
SGOA, which combines simulated annealing (SA) mechanism with the original GOA that is a …
SGOA, which combines simulated annealing (SA) mechanism with the original GOA that is a …
A population state evaluation-based improvement framework for differential evolution
Differential evolution (DE) is one of the most efficient evolutionary algorithms for solving
numerical optimization problems; however, it still suffers from premature convergence and …
numerical optimization problems; however, it still suffers from premature convergence and …
Flood algorithm (FLA): an efficient inspired meta-heuristic for engineering optimization
Introducing a novel meta-heuristic optimization algorithm, the Flood Algorithm (FLA) draws
inspiration from the intricate movement and flow patterns of water masses during flooding …
inspiration from the intricate movement and flow patterns of water masses during flooding …
Improving the search performance of SHADE using linear population size reduction
SHADE is an adaptive DE which incorporates success-history based parameter adaptation
and one of the state-of-the-art DE algorithms. This paper proposes L-SHADE, which further …
and one of the state-of-the-art DE algorithms. This paper proposes L-SHADE, which further …