An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges
As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …
Kepler optimization algorithm: A new metaheuristic algorithm inspired by Kepler's laws of planetary motion
M Abdel-Basset, R Mohamed, SAA Azeem… - Knowledge-based …, 2023 - Elsevier
This study presents a novel physics-based metaheuristic algorithm called Kepler
optimization algorithm (KOA), inspired by Kepler's laws of planetary motion to predict the …
optimization algorithm (KOA), inspired by Kepler's laws of planetary motion to predict the …
Metaheuristics: A Review of Algorithms.
In science and engineering, many optimization tasks are difficult to solve, and the core
concern these days is to apply metaheuristic (MH) algorithms to solve them. Metaheuristics …
concern these days is to apply metaheuristic (MH) algorithms to solve them. Metaheuristics …
A sinh cosh optimizer
Currently, meta-heuristic algorithms have been widely studied and applied, but balancing
exploration and exploitation remains a challenge. In this study, a novel meta-heuristic …
exploration and exploitation remains a challenge. In this study, a novel meta-heuristic …
Mother optimization algorithm: A new human-based metaheuristic approach for solving engineering optimization
This article's innovation and novelty are introducing a new metaheuristic method called
mother optimization algorithm (MOA) that mimics the human interaction between a mother …
mother optimization algorithm (MOA) that mimics the human interaction between a mother …
Comprehensive taxonomies of nature-and bio-inspired optimization: Inspiration versus algorithmic behavior, critical analysis recommendations
In recent algorithmic family simulates different biological processes observed in Nature in
order to efficiently address complex optimization problems. In the last years the number of …
order to efficiently address complex optimization problems. In the last years the number of …
[HTML][HTML] Predicting crystallite size of Mg-Ti-SiC nanocomposites using an adaptive neuro-fuzzy inference system model modified by termite life cycle optimizer
Abstract In this study, Mg-Ti-SiC composite powders with varied micron and nano silicon
carbide (SiC) particle sizes were fabricated utilizing the ball milling technology at various …
carbide (SiC) particle sizes were fabricated utilizing the ball milling technology at various …
Structure damage identification in dams using sparse polynomial chaos expansion combined with hybrid K-means clustering optimizer and genetic algorithm
Structural damage identification plays a crucial role in structural health monitoring. In this
study, a novelty method for structural damage identification is developed, which employs an …
study, a novelty method for structural damage identification is developed, which employs an …
GMO: geometric mean optimizer for solving engineering problems
This paper introduces a new meta-heuristic technique, named geometric mean optimizer
(GMO) that emulates the unique properties of the geometric mean operator in mathematics …
(GMO) that emulates the unique properties of the geometric mean operator in mathematics …
Damage identification in high-rise concrete structures using a bio-inspired meta-heuristic optimization algorithm
In this paper, for the first time, a damage assessment technique for a high-rise concrete
structure is presented. This structure has sixteen stories, a total height of 57 m and its total …
structure is presented. This structure has sixteen stories, a total height of 57 m and its total …