Kepler optimization algorithm: A new metaheuristic algorithm inspired by Kepler’s laws of planetary motion

Knowledge-Based Systems, Год журнала: 2023, Номер 268, С. 110454 - 110454

Опубликована: Март 11, 2023

Язык: Английский

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Genghis Khan shark optimizer: A novel nature-inspired algorithm for engineering optimization

Advanced Engineering Informatics, Год журнала: 2023, Номер 58, С. 102210 - 102210

Опубликована: Окт. 1, 2023

Язык: Английский

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Secretary bird optimization algorithm: a new metaheuristic for solving global optimization problems

Artificial Intelligence Review, Год журнала: 2024, Номер 57(5)

Опубликована: Апрель 23, 2024

Abstract This study introduces a novel population-based metaheuristic algorithm called secretary bird optimization (SBOA), inspired by the survival behavior of birds in their natural environment. Survival for involves continuous hunting prey and evading pursuit from predators. information is crucial proposing new that utilizes abilities to address real-world problems. The algorithm's exploration phase simulates snakes, while exploitation models escape During this phase, observe environment choose most suitable way reach secure refuge. These two phases are iteratively repeated, subject termination criteria, find optimal solution problem. To validate performance SBOA, experiments were conducted assess convergence speed, behavior, other relevant aspects. Furthermore, we compared SBOA with 15 advanced algorithms using CEC-2017 CEC-2022 benchmark suites. All test results consistently demonstrated outstanding terms quality, stability. Lastly, was employed tackle 12 constrained engineering design problems perform three-dimensional path planning Unmanned Aerial Vehicles. demonstrate that, contrasted optimizers, proposed can better solutions at faster pace, showcasing its significant potential addressing

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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Particle guided metaheuristic algorithm for global optimization and feature selection problems

Expert Systems with Applications, Год журнала: 2024, Номер 248, С. 123362 - 123362

Опубликована: Фев. 1, 2024

Язык: Английский

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MSAO: A multi-strategy boosted snow ablation optimizer for global optimization and real-world engineering applications

Advanced Engineering Informatics, Год журнала: 2024, Номер 61, С. 102464 - 102464

Опубликована: Март 15, 2024

Язык: Английский

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Differential evolution algorithms with novel mutations, adaptive parameters, and Weibull flight operator

Soft Computing, Год журнала: 2024, Номер 28(11-12), С. 7039 - 7091

Опубликована: Янв. 20, 2024

Язык: Английский

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Improved dwarf mongoose optimization algorithm using novel nonlinear control and exploration strategies

Expert Systems with Applications, Год журнала: 2023, Номер 233, С. 120904 - 120904

Опубликована: Июнь 29, 2023

Язык: Английский

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Enhanced marine predator algorithm for global optimization and engineering design problems

Advances in Engineering Software, Год журнала: 2023, Номер 184, С. 103517 - 103517

Опубликована: Июнь 28, 2023

Язык: Английский

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Advances in Henry Gas Solubility Optimization: A Physics-Inspired Metaheuristic Algorithm With Its Variants and Applications

IEEE Access, Год журнала: 2024, Номер 12, С. 26062 - 26095

Опубликована: Янв. 1, 2024

The Henry Gas Solubility Optimization (HGSO) is a physics-based metaheuristic inspired by Henry's law, which describes the solubility of gas in liquid under specific pressure conditions. Since its introduction Hashim et al. 2019, HGSO has gained significant attention for unique features, including minimal adaptive parameters and balanced exploration-exploitation trade-off, leading to favorable convergence. This study provides an up-to-date survey HGSO, covering walk through historical development modifications, hybridizations with other algorithms, showcasing adaptability potential synergy. Recent variants are categorized into modified, hybridized, multi-objective versions, review explores main applications, demonstrating effectiveness solving complex problems. evaluation includes discussion algorithm's strengths weaknesses. comprehensive review, featuring graphical tabular comparisons, not only indicates future directions field but also serves as valuable resource researchers seeking deep understanding advanced versions. As algorithms gain prominence intricate optimization problems, this insights applications across diverse domains.

Язык: Английский

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