Enhancement of power quality using UPQC integrated with renewable energy sources through an improved sparrow search-based PID controller DOI Open Access

International Journal of Advanced Technology and Engineering Exploration, Год журнала: 2024, Номер 11(116)

Опубликована: Июль 31, 2024

The production of renewable energy offers several benefits, such as meeting the increasing demand for electricity, facilitating growth clean companies, and enhancing integration nonconventional sources into existing power grid.Solar wind are viable alternatives due to their well-established technological advancements support they receive from government via various initiatives.To meet peak consumer demand,

Язык: Английский

Hybrid quantum particle swarm optimization and variable neighborhood search for flexible job-shop scheduling problem DOI

Yuanxing Xu,

Mengjian Zhang,

Ming Yang

и другие.

Journal of Manufacturing Systems, Год журнала: 2024, Номер 73, С. 334 - 348

Опубликована: Фев. 26, 2024

Язык: Английский

Процитировано

27

Solving multi-objective energy-saving flexible job shop scheduling problem by hybrid search genetic algorithm DOI
L. Hao, Zhiyuan Zou, Xu Liang

и другие.

Computers & Industrial Engineering, Год журнала: 2025, Номер unknown, С. 110829 - 110829

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

1

A survey on sparrow search algorithms and their applications DOI
Jiankai Xue, Bo Shen

International Journal of Systems Science, Год журнала: 2023, Номер 55(4), С. 814 - 832

Опубликована: Дек. 28, 2023

The sparrow search algorithm (SSA) is an efficient swarm-intelligence-based that has made some significant advances since its introduction in 2020. A detailed overview of the basic SSA and several SSA-based variants presented this paper. To be specific, first, principle introduced including mechanism implementation process. Second, many improved SSAs are reviewed hybrid, chaotic, adaptive, binary multi-objective SSAs. In addition, applications real scenarios such as machine learning areas, energy systems, path planning image processing. Finally, further research directions discussed. This survey paper aims to provide a timely review on latest developments

Язык: Английский

Процитировано

16

A multi-mechanism balanced advanced learning sparrow search algorithm for UAV path planning DOI
Chao Yang, Hong Yang, Donglin Zhu

и другие.

Cluster Computing, Год журнала: 2024, Номер 27(5), С. 6623 - 6666

Опубликована: Март 5, 2024

Язык: Английский

Процитировано

4

Analyzing the impact of sustainability on EPQ model: Investigating price and sustainability level dependent demand using center-radius optimization techniques with Metaheuristic algorithms in interval valued environment DOI Open Access
Mamta Keswani, Vinita Dwivedi, Uttam Kumar Khedlekar

и другие.

Journal of Industrial and Management Optimization, Год журнала: 2025, Номер 0(0), С. 0 - 0

Опубликована: Янв. 1, 2025

In real-world production inventory systems, uncertainties related to demand, production, defectiveness, and costs pose significant challenges. These uncertainties—arising from incomplete information, unpredictability, complexity, or system variability—complicate decision-making planning. To address these challenges, various methodologies, including interval, fuzzy, stochastic, fuzzy-stochastic approaches, have been developed. The interval-based approach, in particular, provides a practical way represent uncertainty, encompassing factors like epistemic which arises inherent randomness variability. This study introduces green model within an framework, incorporating interval-valued representations of defective rates stochastic demand. Differential equations governing levels are formulated interval form solved using advanced parametric techniques. Unlike traditional models that focus on cost minimization profit maximization, this paper adopts optimization approach centered the profit-cost ratio function, reflecting negative relationship between rate hand sharpening manufacturer's goal. also explores business practice 'buy now, pay later' (BNPL), technically delay-in-payments is used boost sales. BNPL scheme integrated into model, problem through center-radius technique. Metaheuristic algorithms employed derive optimal solution. A numerical example validates while sensitivity analyses explore variations algorithmic parameters. Statistical analysis ANOVA tests further supports findings. case illustrates how concept can be practice, with Maple Python. comprehensive highlights model's effectiveness managing uncertainty optimizing performance systems.

Язык: Английский

Процитировано

0

A comprehensive survey of golden jacal optimization and its applications DOI
Mehdi Hosseinzadeh, Jawad Tanveer, Amir Masoud Rahmani

и другие.

Computer Science Review, Год журнала: 2025, Номер 56, С. 100733 - 100733

Опубликована: Фев. 11, 2025

Язык: Английский

Процитировано

0

A novel inversion approach for seepage parameter of concrete face rockfill dams based on an enhanced sparrow search algorithm DOI
Yuan Ping Feng,

Bin Tian,

Zhenzhong Shen

и другие.

Computers and Geotechnics, Год журнала: 2025, Номер 183, С. 107214 - 107214

Опубликована: Март 28, 2025

Язык: Английский

Процитировано

0

A sparrow search algorithm optimized GAN-stacking model for the evaluation of geothermal resource potential assessment DOI
Haibin Li, Yang Yang, Qiang Xu

и другие.

Geothermics, Год журнала: 2025, Номер 131, С. 103398 - 103398

Опубликована: Май 28, 2025

Язык: Английский

Процитировано

0

Optimization of Regenerative Braking Control Strategy in Single-Pedal Mode Based on Electro-Mechanical Braking DOI Creative Commons
Xiaobin Ning, Zhenghao Wang, Yong Lin

и другие.

IEEE Access, Год журнала: 2024, Номер 12, С. 170994 - 171014

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

2

MLBRSA: Multi-Learning-Based Reptile Search Algorithm for Global Optimization and Software Requirement Prioritization Problems DOI Creative Commons

Jeyaganesh Kumar Kailasam,

Rajkumar Nalliah, N. M. Saravana Kumar

и другие.

Biomimetics, Год журнала: 2023, Номер 8(8), С. 615 - 615

Опубликована: Дек. 15, 2023

In the realm of computational problem-solving, search for efficient algorithms tailored real-world engineering challenges and software requirement prioritization is relentless. This paper introduces Multi-Learning-Based Reptile Search Algorithm (MLBRSA), a novel approach that synergistically integrates Q-learning, competitive learning, adaptive learning techniques. The essence multi-learning lies in harnessing strengths these individual paradigms to foster more robust versatile mechanism. Q-learning brings advantage reinforcement enabling algorithm make informed decisions based on past experiences. On other hand, an element competition, ensuring best solutions are continually evolving adapting. Lastly, ensures remains flexible, adjusting traditional (RSA) parameters. application MLBRSA numerical benchmarks few problems demonstrates its ability find optimal complex problem spaces. Furthermore, when applied complicated task prioritization, showcases capability rank requirements effectively, critical functionalities addressed promptly. Based results obtained, stands as evidence potential multi-learning, offering promising solution software-centric challenges. Its adaptability, competitiveness, experience-driven it valuable tool researchers practitioners.

Язык: Английский

Процитировано

5