Greylag goose optimization: Nature-inspired optimization algorithm
Nature-inspired metaheuristic approaches draw their core idea from biological evolution in
order to create new and powerful competing algorithms. Such algorithms can be divided into …
order to create new and powerful competing algorithms. Such algorithms can be divided into …
Nature-inspired optimization algorithms and their significance in multi-thresholding image segmentation: an inclusive review
Multilevel Thresholding (MLT) is considered as a significant and imperative research field in
image segmentation that can efficiently resolve difficulties aroused while analyzing the …
image segmentation that can efficiently resolve difficulties aroused while analyzing the …
Metaheuristic optimization algorithms: A comprehensive overview and classification of benchmark test functions
This review aims to exploit a study on different benchmark test functions used to evaluate the
performance of Meta-Heuristic (MH) optimization techniques. The performance of the MH …
performance of Meta-Heuristic (MH) optimization techniques. The performance of the MH …
Snow ablation optimizer: A novel metaheuristic technique for numerical optimization and engineering design
L Deng, S Liu - Expert Systems with Applications, 2023 - Elsevier
This paper develops a novel nature-inspired metaheuristic technique named snow ablation
optimizer (SAO) for numerical optimization and engineering design. The SAO algorithm …
optimizer (SAO) for numerical optimization and engineering design. The SAO algorithm …
Hunger games pattern search with elite opposite-based solution for solving complex engineering design problems
The hunger games search (HGS) algorithm is designed to tackle optimization problems,
however, issues such as local minimum stagnation and immature convergence hinder its …
however, issues such as local minimum stagnation and immature convergence hinder its …
Fuzzy-based hunger games search algorithm for global optimization and feature selection using medical data
Feature selection (FS) is one of the basic data preprocessing steps in data mining and
machine learning. It is used to reduce feature size and increase model generalization. In …
machine learning. It is used to reduce feature size and increase model generalization. In …
[HTML][HTML] Novel hybrid of AOA-BSA with double adaptive and random spare for global optimization and engineering problems
Abstract Archimedes Optimization Algorithm (AOA) is a new physics-based optimizer that
simulates Archimedes principles. AOA has been used in a variety of real-world applications …
simulates Archimedes principles. AOA has been used in a variety of real-world applications …
A novel improved chef-based optimization algorithm with Gaussian random walk-based diffusion process for global optimization and engineering problems
FK Onay - Mathematics and Computers in Simulation, 2023 - Elsevier
The chef-based optimization algorithm (CBOA) is a human-based method inspired by the
relationship between culinary students and chef instructors. The original CBOA does not …
relationship between culinary students and chef instructors. The original CBOA does not …
A novel version of slime mould algorithm for global optimization and real world engineering problems: Enhanced slime mould algorithm
The slime mould algorithm is a stochastic optimization algorithm based on the oscillation
mode of nature's slime mould, and it has effective convergence. On the other hand, it gets …
mode of nature's slime mould, and it has effective convergence. On the other hand, it gets …
Improved reptile search optimization algorithm using chaotic map and simulated annealing for feature selection in medical field
The increased volume of medical datasets has produced high dimensional features,
negatively affecting machine learning (ML) classifiers. In ML, the feature selection process is …
negatively affecting machine learning (ML) classifiers. In ML, the feature selection process is …