An enhanced ivy algorithm fusing multiple strategies for global optimization problems

Advances in Engineering Software, Год журнала: 2025, Номер 203, С. 103862 - 103862

Опубликована: Фев. 6, 2025

Язык: Английский

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FOX Optimization Algorithm Based on Adaptive Spiral Flight and Multi-Strategy Fusion

Biomimetics, Год журнала: 2024, Номер 9(9), С. 524 - 524

Опубликована: Авг. 30, 2024

Adaptive spiral flight and multi-strategy fusion are the foundations of a new FOX optimization algorithm that aims to address drawbacks original method, including weak starting individual ergodicity, low diversity, an easy way slip into local optimum. In order enhance population, inertial weight is added along with Levy variable strategy once population initialized using tent chaotic map. To begin process implementing fox position created Tent map in provide more ergodic varied beginning locations. improve quality solution, second place. The random walk mode then updated updating approach. Subsequently, algorithm’s global searches balanced, flying method greedy approach incorporated update location. enhanced technique thoroughly contrasted various swarm intelligence algorithms engineering application issues CEC2017 benchmark test functions. According simulation findings, there have been notable advancements convergence speed, accuracy, stability, as well jumping out optimum, upgraded algorithm.

Язык: Английский

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Enhancing Solid Oxide Fuel Cell Efficiency Through Advanced Model Identification Using Differential Evolutionary Mutation Fennec Fox Algorithm

International Journal of Computational Intelligence Systems, Год журнала: 2025, Номер 18(1)

Опубликована: Фев. 24, 2025

Fuel cells (FCs) are increasingly attracting attention for their efficient conversion of chemical energy into electricity without the need combustion. Their high efficiency and versatility make them a promising technology across various applications. Researchers actively exploring ways to optimize FC systems meet specific needs. Among different types fuel cells, solid oxide (SOFCs) stand out as clean that generates through electrochemical reactions. However, accurately modeling SOFCs, which is essential reducing design costs, presents challenge due complex nonlinear characteristics. An ideal model should be adaptable varying operating pressures temperatures. This research introduces novel approach optimal SOFC identification using differential evolutionary mutation Fennec fox algorithm (DEMFFA). A real-world case study demonstrates superior effectiveness DEMFFA compared existing methods. Additionally, sensitivity analysis evaluates influence temperature pressure on model, with results indicating proposed method achieves higher than other approaches. The sum square error 1.18E-11 followed by parent algorithm, (FFA) (1.24E-09), some algorithms. computational time 1.001 s, FFA (1.199 s) offers significant potential, enhancing renewable energy, minimizing SOFC's environmental impact, improving applications like distributed power generation hydrogen integration.

Язык: Английский

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A survey of Beluga whale optimization and its variants: Statistical analysis, advances, and structural reviewing

Computer Science Review, Год журнала: 2025, Номер 57, С. 100740 - 100740

Опубликована: Март 3, 2025

Язык: Английский

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CMRLCCOA: Multi-Strategy Enhanced Coati Optimization Algorithm for Engineering Designs and Hypersonic Vehicle Path Planning

Biomimetics, Год журнала: 2024, Номер 9(7), С. 399 - 399

Опубликована: Июль 1, 2024

The recently introduced coati optimization algorithm suffers from drawbacks such as slow search velocity and weak precision. An enhanced called CMRLCCOA is proposed. Firstly, the Sine chaotic mapping function used to initialize a way obtain better-quality populations increase diversity of population. Secondly, generated candidate solutions are updated again using convex lens imaging reverse learning strategy expand range. Thirdly, Lévy flight increases step size, expands range, avoids phenomenon convergence too early. Finally, utilizing crossover can effectively reduce blind spots, making particles constantly close global optimum solution. four strategies work together enhance efficiency COA boost precision steadiness. performance evaluated on CEC2017 CEC2019. superiority comprehensively demonstrated by comparing output with previously submitted algorithms. Besides results iterative curves, boxplots nonparametric statistical analysis illustrate that competitive, significantly improves accuracy, well local optimal solutions. usefulness proven through three engineering application problems. A mathematical model hypersonic vehicle cruise trajectory problem developed. result less than other comparative algorithms shortest path length for this obtained.

Язык: Английский

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DHRDE: Dual-population hybrid update and RPR mechanism based differential evolutionary algorithm for engineering applications

Computer Methods in Applied Mechanics and Engineering, Год журнала: 2024, Номер 431, С. 117251 - 117251

Опубликована: Авг. 16, 2024

Язык: Английский

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