Tactical flight optimizer: a novel optimization technique tested on mathematical, mechanical, and structural optimization problems

Materials Testing, Год журнала: 2025, Номер 67(2), С. 330 - 352

Опубликована: Янв. 22, 2025

Abstract The current study presents a novel gradient-free metaheuristic search algorithm named Tactical Flight Optimizer (TFO), tailored to meet the growing need for high-performance optimization techniques in solving complex engineering and mathematical problems. main contribution of this is development method that simulates tactical air combat formations, offering sophisticated alternative conventional algorithms. In proposed method, location each agent updated based on resultant vector derived from three updating vectors. vectors incorporate total information stored by agents iteration. Consequently, navigation process guided more logical mechanism rather than simple random process. performance TFO initially benchmarked set constrained functions. Subsequently, it evaluated addressing suite mechanical structural problems, containing both discrete continuous decision variables. obtained results are compared with five other well-stablished techniques. Acquired numerical indicate can provide promising problems terms computational cost, accuracy, stability.

Язык: Английский

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Simultaneous optimization of capacity and topology of seismic isolation systems in multi-story buildings using a fuzzy reinforced differential evolution method

Advances in Engineering Software, Год журнала: 2024, Номер 198, С. 103781 - 103781

Опубликована: Сен. 27, 2024

Язык: Английский

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An arithmetic optimization algorithm based on opposition jumping rate for time cost trade-off optimization problems

Asian Journal of Civil Engineering, Год журнала: 2024, Номер unknown

Опубликована: Ноя. 29, 2024

Язык: Английский

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A novel type-2 decision mechanism for dynamic parameter adaptation: theory and application in mathematical and structural problems

Neural Computing and Applications, Год журнала: 2024, Номер 36(31), С. 19729 - 19757

Опубликована: Авг. 8, 2024

Abstract Metaheuristic algorithms are stochastic-based search techniques widely used for solving different types of optimization problems. These methods mostly adjust their behavior using pre-defined pattern(s) regardless the current problem specifications. Therefore, integrating them with logical auxiliary modules can significantly enhance efficiency by enabling to dynamically adapt behavior. The present study introduces a novel decision-making approach that employs interval type-2 fuzzy logic balance during process. proposed approach, designed as stand-alone module flexibility be integrated into various algorithms, is incorporated Interactive Search Algorithm. developed reinforced technique named Type-2 Fuzzy Performance method tested on unconstrained mathematical functions and constrained structural mechanical attained results compared standard ISA seven other metaheuristic through suite numerical statistical evaluations. Drawing from obtained results, integration decision enhances algorithm's capability. This improvement evident in terms stability, accuracy, computational cost. It worth noting employed comparative performance index indicates improvements 3.38, 13.09, 16.61, 27.23 percent best solution found selected engineering

Язык: Английский

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Optimal directed acyclic graph federated learning model for energy-efficient IoT communication networks

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

Опубликована: Сен. 28, 2024

Язык: Английский

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