Black-winged kite algorithm: a nature-inspired meta-heuristic for solving benchmark functions and engineering problems

Artificial Intelligence Review, Год журнала: 2024, Номер 57(4)

Опубликована: Март 23, 2024

Abstract This paper innovatively proposes the Black Kite Algorithm (BKA), a meta-heuristic optimization algorithm inspired by migratory and predatory behavior of black kite. The BKA integrates Cauchy mutation strategy Leader to enhance global search capability convergence speed algorithm. novel combination achieves good balance between exploring solutions utilizing local information. Against standard test function sets CEC-2022 CEC-2017, as well other complex functions, attained best performance in 66.7, 72.4 77.8% cases, respectively. effectiveness is validated through detailed analysis statistical comparisons. Moreover, its application solving five practical engineering design problems demonstrates potential addressing constrained challenges real world indicates that it has significant competitive strength comparison with existing techniques. In summary, proven value advantages variety due excellent performance. source code publicly available at https://www.mathworks.com/matlabcentral/fileexchange/161401-black-winged-kite-algorithm-bka .

Язык: Английский

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Chaotic marine predators algorithm for global optimization of real-world engineering problems

Knowledge-Based Systems, Год журнала: 2022, Номер 261, С. 110192 - 110192

Опубликована: Дек. 15, 2022

Язык: Английский

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Improved Metaheuristic-Driven Energy-Aware Cluster-Based Routing Scheme for IoT-Assisted Wireless Sensor Networks

Sustainability, Год журнала: 2022, Номер 14(13), С. 7712 - 7712

Опубликована: Июнь 24, 2022

The Internet of Things (IoT) is a network numerous devices that are consistent with one another via the internet. Wireless sensor networks (WSN) play an integral part in IoT, which helps to produce seamless data highly influence network’s lifetime. Despite significant applications several challenging issues such as security, energy, load balancing, and storage exist. Energy efficiency considered be vital design IoT-assisted WSN; this accomplished by clustering multi-hop routing techniques. In view this, we introduce improved metaheuristic-driven energy-aware cluster-based (IMD-EACBR) scheme for WSN. proposed IMD-EACBR model intends achieve maximum energy utilization lifetime network. order attain primarily designs Archimedes optimization algorithm-based (IAOAC) technique cluster head (CH) election organization. addition, IAOAC algorithm computes suitability purpose connects multiple structures specifically efficiency, detachment, node degree, inter-cluster distance. Moreover, teaching–learning-based (TLBO) (TLBO-MHR) applied optimum selection routes destinations. Furthermore, TLBO-MHR method originates using distance metrics. performance has been examined aspects. Simulation outcomes demonstrated enhancements over recent state-of-the-art approaches. transmission emergency data, based on requirements hop count end, subjected rigorous testing NS-3.26’s full simulation capabilities. results reveal improvements terms proportion dead nodes, network, amount consumed, packet delivery ratio (PDR), latency.

Язык: Английский

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An Improved Harris Hawks Optimization Algorithm with Multi-strategy for Community Detection in Social Network

Journal of Bionic Engineering, Год журнала: 2022, Номер 20(3), С. 1175 - 1197

Опубликована: Дек. 19, 2022

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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Boosting particle swarm optimization by backtracking search algorithm for optimization problems

Swarm and Evolutionary Computation, Год журнала: 2023, Номер 79, С. 101304 - 101304

Опубликована: Март 26, 2023

Язык: Английский

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Metaheuristic optimization algorithms: a comprehensive overview and classification of benchmark test functions

Soft Computing, Год журнала: 2023, Номер 28(4), С. 3123 - 3186

Опубликована: Окт. 11, 2023

Язык: Английский

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Red-tailed hawk algorithm for numerical optimization and real-world problems

Scientific Reports, Год журнала: 2023, Номер 13(1)

Опубликована: Авг. 9, 2023

This study suggests a new nature-inspired metaheuristic optimization algorithm called the red-tailed hawk (RTH). As predator, has hunting strategy from detecting prey until swoop stage. There are three stages during process. In high soaring stage, explores search space and determines area with location. low moves inside selected around to choose best position for hunt. Then, swings hits its target in stooping swooping stages. The proposed mimics prey-hunting method of solving real-world problems. performance RTH been evaluated on classes first class includes specific kinds problems: 22 standard benchmark functions, including unimodal, multimodal, fixed-dimensional multimodal IEEE Congress Evolutionary Computation 2020 (CEC2020), CEC2022. is compared eight recent algorithms confirm contribution these considered Farmland Fertility Optimizer (FO), African Vultures Optimization Algorithm (AVOA), Mountain Gazelle (MGO), Gorilla Troops (GTO), COOT algorithm, Hunger Games Search (HGS), Aquila (AO), Harris Hawks (HHO). results regarding accuracy, robustness, convergence speed. second seven engineering problems that will be investigate other published profoundly. Finally, proton exchange membrane fuel cell (PEMFC) extraction parameters performed evaluate complex problem. several papers approve performance. ultimate each ability provide higher most cases. For class, mostly got optimal solutions functions faster provided better third when resolving real word or extracting PEMFC parameters.

Язык: Английский

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Synergizing the enhanced RIME with fuzzy K-nearest neighbor for diagnose of pulmonary hypertension

Computers in Biology and Medicine, Год журнала: 2023, Номер 165, С. 107408 - 107408

Опубликована: Авг. 29, 2023

Язык: Английский

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Artemisinin optimization based on malaria therapy: Algorithm and applications to medical image segmentation

Displays, Год журнала: 2024, Номер 84, С. 102740 - 102740

Опубликована: Май 4, 2024

Язык: Английский

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