An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges

Artificial Intelligence Review, Год журнала: 2023, Номер 56(11), С. 13187 - 13257

Опубликована: Апрель 9, 2023

Язык: Английский

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Electric eel foraging optimization: A new bio-inspired optimizer for engineering applications

Expert Systems with Applications, Год журнала: 2023, Номер 238, С. 122200 - 122200

Опубликована: Окт. 23, 2023

Язык: Английский

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MEALPY: An open-source library for latest meta-heuristic algorithms in Python

Journal of Systems Architecture, Год журнала: 2023, Номер 139, С. 102871 - 102871

Опубликована: Апрель 6, 2023

Язык: Английский

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Light Spectrum Optimizer: A Novel Physics-Inspired Metaheuristic Optimization Algorithm

Mathematics, Год журнала: 2022, Номер 10(19), С. 3466 - 3466

Опубликована: Сен. 23, 2022

This paper introduces a novel physical-inspired metaheuristic algorithm called “Light Spectrum Optimizer (LSO)” for continuous optimization problems. The inspiration the proposed is light dispersions with different angles while passing through rain droplets, causing meteorological phenomenon of colorful rainbow spectrum. In order to validate algorithm, three experiments are conducted. First, LSO tested on solving CEC 2005, and obtained results compared wide range well-regarded metaheuristics. second experiment, used four competitions in single objective benchmarks (CEC2014, CEC2017, CEC2020, CEC2022), its eleven well-established recently-published optimizers, named grey wolf optimizer (GWO), whale (WOA), salp swarm (SSA), evolutionary algorithms like differential evolution (DE), optimizers including gradient-based (GBO), artificial gorilla troops (GTO), Runge–Kutta method (RUN) beyond metaphor, African vultures (AVOA), equilibrium (EO), Reptile Search Algorithm (RSA), slime mold (SMA). addition, several engineering design problems solved, many from literature. experimental statistical analysis demonstrate merits highly superior performance algorithm.

Язык: Английский

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Quadratic Interpolation Optimization (QIO): A new optimization algorithm based on generalized quadratic interpolation and its applications to real-world engineering problems

Computer Methods in Applied Mechanics and Engineering, Год журнала: 2023, Номер 417, С. 116446 - 116446

Опубликована: Сен. 28, 2023

Язык: Английский

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Optimization based on performance of lungs in body: Lungs performance-based optimization (LPO)

Computer Methods in Applied Mechanics and Engineering, Год журнала: 2023, Номер 419, С. 116582 - 116582

Опубликована: Ноя. 21, 2023

Язык: Английский

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Optimal truss design with MOHO: A multi-objective optimization perspective

PLoS ONE, Год журнала: 2024, Номер 19(8), С. e0308474 - e0308474

Опубликована: Авг. 19, 2024

This research article presents the Multi-Objective Hippopotamus Optimizer (MOHO), a unique approach that excels in tackling complex structural optimization problems. The (HO) is novel meta-heuristic methodology draws inspiration from natural behaviour of hippos. HO built upon trinary-phase model incorporates mathematical representations crucial aspects Hippo's behaviour, including their movements aquatic environments, defense mechanisms against predators, and avoidance strategies. conceptual framework forms basis for developing multi-objective (MO) variant MOHO, which was applied to optimize five well-known truss structures. Balancing safety precautions size constraints concerning stresses on individual sections constituent parts, these problems also involved competing objectives, such as reducing weight structure maximum nodal displacement. findings six popular methods were used compare results. Four industry-standard performance measures this comparison qualitative examination finest Pareto-front plots generated by each algorithm. average values obtained Friedman rank test analysis unequivocally showed MOHO outperformed other resolving significant quickly. In addition finding preserving more Pareto-optimal sets, recommended algorithm produced excellent convergence variance objective decision fields. demonstrated its potential navigating objectives through diversity analysis. Additionally, swarm effectively visualize MOHO's solution distribution across iterations, highlighting superior behaviour. Consequently, exhibits promise valuable method issues.

Язык: Английский

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Optimization based on the smart behavior of plants with its engineering applications: Ivy algorithm

Knowledge-Based Systems, Год журнала: 2024, Номер 295, С. 111850 - 111850

Опубликована: Апрель 22, 2024

Язык: Английский

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Tornado optimizer with Coriolis force: a novel bio-inspired meta-heuristic algorithm for solving engineering problems

Artificial Intelligence Review, Год журнала: 2025, Номер 58(4)

Опубликована: Фев. 5, 2025

Язык: Английский

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A hierarchical multi-leadership sine cosine algorithm to dissolving global optimization and data classification: The COVID-19 case study

Computers in Biology and Medicine, Год журнала: 2023, Номер 164, С. 107212 - 107212

Опубликована: Июль 6, 2023

Язык: Английский

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