Enhancing sand cat swarm optimization based on multi-strategy mixing for solving engineering optimization problems DOI
Wenchuan Wang, Zheng Han, Zhao Zhang

и другие.

Evolutionary Intelligence, Год журнала: 2024, Номер 18(1)

Опубликована: Ноя. 16, 2024

Язык: Английский

Uncertain utility portfolio optimization based on two different criteria and improved whale optimization algorithm DOI
Jiajun Xu, Bo Li

Expert Systems with Applications, Год журнала: 2025, Номер 268, С. 126281 - 126281

Опубликована: Янв. 2, 2025

Язык: Английский

Процитировано

0

Optimization of multi-pass coating for magnetic-thermal-assisted laser cladding based on data-enhanced WOA-DE-TELM and LHS-AMOPSO algorithm DOI

Jiangtao Gong,

Haiqing Li,

Helong Yu

и другие.

Surface and Coatings Technology, Год журнала: 2025, Номер 497, С. 131765 - 131765

Опубликована: Янв. 10, 2025

Язык: Английский

Процитировано

0

IWOA-RNN: An improved whale optimization algorithm with recurrent neural networks for traffic flow prediction DOI Creative Commons
Zhiyou Liu,

Xinbin Li,

Zhigang Lu

и другие.

Alexandria Engineering Journal, Год журнала: 2025, Номер 117, С. 563 - 576

Опубликована: Янв. 20, 2025

Язык: Английский

Процитировано

0

Stability framework for off-grid hydrogen production systems: Coordinated control of steady-state source-load balancing and transient frequency response DOI

Yongxin Lu,

Guotian Yang, Jianguo Liu

и другие.

Applied Energy, Год журнала: 2025, Номер 390, С. 125807 - 125807

Опубликована: Апрель 2, 2025

Язык: Английский

Процитировано

0

Economic optimization of business administration resources: Multi-objective scheduling method based on improved PSO DOI

Sizheng Li

Journal of Computational Methods in Sciences and Engineering, Год журнала: 2025, Номер unknown

Опубликована: Апрель 24, 2025

In the context of increasing environmental challenges and demand for sustainable development, traditional resource scheduling models in business management often fail to balance economic efficiency with constraints. To address this gap, study proposes an enhanced Particle Swarm Optimization (PSO) algorithm, termed OBLPSO, which integrates Opposition-Based Learning (OBL) a perturbation mechanism. First, OBL generates high-quality initial population improve solution diversity, while cosine curve adaptive strategy dynamically adjusts inertia weights global exploration local exploitation. Additionally, mechanism expands search range, preventing premature convergence. A multi-objective optimization model is established, incorporating task time, cost, impact (e.g., energy consumption pollutant emissions) maximize utilization minimize ecological harm. Experimental results demonstrate that OBLPSO reduces processing time by 29.7% 16.1% compared benchmark algorithms ACO, GA, standard PSO) under large-scale tasks (2000 tasks). The proposed method provides robust enterprise environment

Язык: Английский

Процитировано

0

Shared manufacturing service composition optimization based on IGWO-GA algorithm DOI
Peng Liu,

Jiating Liang,

Caiyun Liu

и другие.

International Journal of Management Science and Engineering Management, Год журнала: 2025, Номер unknown, С. 1 - 11

Опубликована: Апрель 30, 2025

Язык: Английский

Процитировано

0

Enhancing the power quality in radial electrical systems using optimal sizing and selective allocation of distributed generations DOI Creative Commons
Bachirou Bogno, Deli Goron,

Nisso Nicodem

и другие.

PLoS ONE, Год журнала: 2024, Номер 19(12), С. e0316281 - e0316281

Опубликована: Дек. 30, 2024

Optimizing energy resources is a major priority these days. Increasing household demand often leads to the deterioration of poorly sized distribution networks. This paper presents method for compensation and optimization in radial systems (ORDS). By integrating distributed generations (DG), an approach used evaluate voltage power profiles, as well losses on (PLRDSs). After generations, improved profiles are established. A potential solution blackouts (PCB) can also be use hybrid generation (HDGSs) that reinforce networks (RDNs) by improving quality. Accordingly, proposed configuration system shown this work inject multiple renewable sources (MRES) from selected regulated nodes. The feasibility evaluated using particle swarm (PSO), which was locate stable nodes locations, sensitive fluctuations. based evaluation IEEE 33 bus 69 standards MATLAB-based establishes objective function converges more quickly optimal results.

Язык: Английский

Процитировано

2

Enhancing sand cat swarm optimization based on multi-strategy mixing for solving engineering optimization problems DOI
Wenchuan Wang, Zheng Han, Zhao Zhang

и другие.

Evolutionary Intelligence, Год журнала: 2024, Номер 18(1)

Опубликована: Ноя. 16, 2024

Язык: Английский

Процитировано

0