Application of an Improved Differential Evolution Algorithm in Practical Engineering

Concurrency and Computation Practice and Experience, Год журнала: 2025, Номер 37(3)

Опубликована: Янв. 20, 2025

ABSTRACT The differential evolution algorithm, as a simple yet effective random search often faces challenges in terms of rapid convergence and sharp decline population diversity during the evolutionary process. To address this issue, an improved namely multi‐population collaboration (MPC‐DE) is introduced article. algorithm proposes mechanism two‐stage mutation operator. Through mechanism, individuals involved effectively controlled, enhancing algorithm's global capability. operator efficiently balances requirements exploration exploitation stages. Additionally, perturbation to enhance ability escape local optima improve stability. By conducting comprehensive comparisons with 15 well‐known optimization algorithms on CEC2005 CEC2017 test functions, MPC‐DE thoroughly evaluated solution accuracy, convergence, stability, scalability. Furthermore, validation 57 real‐world engineering problems CEC2020 demonstrates robustness MPC‐DE. Experimental results reveal that, compared other algorithms, exhibits superior accuracy both constrained unconstrained problems. These research findings provide strong support for widespread applicability addressing practical

Язык: Английский

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Enhancing monthly runoff prediction: a data-driven framework integrating variational mode decomposition, enhanced artificial rabbit optimization, support vector regression, and error correction

Earth Science Informatics, Год журнала: 2025, Номер 18(3)

Опубликована: Фев. 17, 2025

Язык: Английский

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Harnessing dynamic turbulent dynamics in parrot optimization algorithm for complex high-dimensional engineering problems

Computer Methods in Applied Mechanics and Engineering, Год журнала: 2025, Номер 440, С. 117908 - 117908

Опубликована: Март 19, 2025

Язык: Английский

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Dynamic Agricultural Pest Classification Using Enhanced SAO-CNN and Swarm Intelligence Optimization for UAVs

International Journal of Cognitive Computing in Engineering, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Язык: Английский

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GPSOM: group-based particle swarm optimization with multiple strategies for engineering applications

Journal Of Big Data, Год журнала: 2025, Номер 12(1)

Опубликована: Май 9, 2025

Язык: Английский

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Comprehensive Adaptive Enterprise Optimization Algorithm and Its Engineering Applications

Biomimetics, Год журнала: 2025, Номер 10(5), С. 302 - 302

Опубликована: Май 9, 2025

In this study, a brand-new algorithm called the Comprehensive Adaptive Enterprise Development Optimizer (CAED) is proposed to overcome drawbacks of (ED) in complex optimization tasks. particular, it aims tackle problems slow convergence and low precision. To enhance algorithm’s ability break free from local optima, lens imaging reverse learning approach incorporated. This creates solutions by utilizing concepts optical imaging. As result, expands search range boosts probability finding superior beyond optima. Moreover, an environmental sensitivity-driven adaptive inertial weight developed. dynamically modifies equilibrium between global exploration, which enables for new promising areas solution space, development, centered on refining close currently best-found areas. evaluate efficacy CAED, 23 benchmark functions CEC2005 are chosen testing. The performance CAED contrasted with that nine other algorithms, such as Particle Swarm Optimization (PSO), Gray Wolf (GWO), Antlion (AOA). Experimental findings show unimodal functions, standard deviation almost 0, reflects its high accuracy stability. case multimodal optimal value obtained notably better than those further emphasizing outstanding performance. also applied engineering challenges, like design cantilever beams three-bar trusses. For beam problem, achieved 13.3925, merely 0.0098. truss 259.805047, extremely small 1.11 × 10−7. These results much traditional ED comparative algorithms. Overall, through coordinated implementation multiple strategies, exhibits precision, strong robustness, rapid when searching spaces. such, offers efficient solving various problems.

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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GSRPSO: A multi-strategy integrated particle swarm algorithm for multi-threshold segmentation of real cervical cancer images

Swarm and Evolutionary Computation, Год журнала: 2024, Номер 91, С. 101766 - 101766

Опубликована: Окт. 31, 2024

Язык: Английский

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MGCHMO: A dynamic differential human memory optimization with Cauchy and Gauss mutation for solving engineering problems

Advances in Engineering Software, Год журнала: 2024, Номер 198, С. 103793 - 103793

Опубликована: Окт. 22, 2024

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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