Sub-population evolutionary particle swarm optimization with dynamic fitness-distance balance and elite reverse learning for engineering design problems

Advances in Engineering Software, Год журнала: 2025, Номер 202, С. 103866 - 103866

Опубликована: Янв. 30, 2025

Язык: Английский

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A spherical vector-based adaptive evolutionary particle swarm optimization for UAV path planning under threat conditions

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 16, 2025

Unmanned aerial vehicle (UAV) path planning is a constrained multi-objective optimization problem. With the increasing scale of UAV applications, finding an efficient and safe in complex real-world environments crucial. However, existing particle swarm (PSO) algorithms struggle with these problems as they fail to consider dynamics, resulting many infeasible solutions poor convergence optimal solutions. To address challenges, we propose spherical vector-based adaptive evolutionary (SAEPSO) algorithm. This algorithm, based on vectors, directly incorporates dynamic constraints introduces improved tent map reverse learning enhance diversity distribution initial Additionally, nonlinear factors are integrated balance exploration exploitation capabilities. avoid local optima highly environments, acceleration strategy for particles, programming incorporated further improve capability. Finally, conducted comparative studies six benchmark scenarios varying threat levels, results demonstrated that proposed algorithm outperforms others solution effectiveness, final accuracy, stability, scalability.

Язык: Английский

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Hybrid remora crayfish optimization for engineering and wireless sensor network coverage optimization

Cluster Computing, Год журнала: 2024, Номер 27(7), С. 10141 - 10168

Опубликована: Май 4, 2024

Язык: Английский

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Cumulative Major Advances in Particle Swarm Optimization from 2018 to the Present: Variants, Analysis and Applications

Archives of Computational Methods in Engineering, Год журнала: 2025, Номер unknown

Опубликована: Янв. 22, 2025

Язык: Английский

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DRPSO:A multi-strategy fusion particle swarm optimization algorithm with a replacement mechanisms for colon cancer pathology image segmentation

Computers in Biology and Medicine, Год журнала: 2024, Номер 178, С. 108780 - 108780

Опубликована: Июнь 22, 2024

Язык: Английский

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Innovative heat management method and metaheuristic algorithm optimized power supply-demand balance for PEMFC-ASHP-CHP system

Applied Energy, Год журнала: 2024, Номер 371, С. 123778 - 123778

Опубликована: Июнь 24, 2024

Язык: Английский

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An Opposition-Based Learning Adaptive Chaotic Particle Swarm Optimization Algorithm

Journal of Bionic Engineering, Год журнала: 2024, Номер unknown

Опубликована: Сен. 4, 2024

Язык: Английский

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Improved marine predators algorithm for engineering design optimization problems

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Июнь 6, 2024

Abstract The Marine Predator Algorithm (MPA) has unique advantages as an important branch of population-based algorithms. However, it emerges more disadvantages gradually, such traps to local optima, insufficient diversity, and premature convergence, when dealing with complex problems in practical industrial engineering design applications. In response these limitations, this paper proposes a novel Improved (IMPA). By introducing adaptive weight adjustment strategy dynamic social learning mechanism, study significantly improves the encounter frequency efficiency between predators preys marine ecosystems. performance IMPA was evaluated through benchmark functions, CEC2021 suite problems, including welded beam design, tension/compression spring pressure vessel three-bar design. results indicate that achieved significant success optimization process over other methods, exhibiting excellent both solving optimal parameter solutions optimizing objective function values. performs well terms accuracy robustness, which also proves its successfully problems.

Язык: Английский

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Ultra-high-precision pneumatic force servo system based on a novel improved particle swarm optimization algorithm integrating Gaussian mutation and fuzzy theory

ISA Transactions, Год журнала: 2024, Номер 152, С. 453 - 466

Опубликована: Июнь 30, 2024

Язык: Английский

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Multi-strategy improved seagull optimization algorithm and its application in practical engineering

Engineering Optimization, Год журнала: 2024, Номер unknown, С. 1 - 39

Опубликована: Июль 24, 2024

Metaheuristic algorithms play a crucial role in engineering optimization, as they can find the optimal parameter configuration systems. This article proposes multi-strategy improved seagull optimization algorithm (OPSOA) to solve application problems. Aiming problems of slow search speed and low convergence accuracy standard (SOA), four strategies, including Lévy flight Cauchy mutation, were introduced improve its performance. Comparison shows that OPSOA incomplete are better than SOA, indicating each improvement is effective. By testing benchmark functions CEC 2017 2022, it shown has strong ability solution superior other terms speed. The this practical proves significant advantages solving complex

Язык: Английский

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