Scheduling of Multisensor for UAV Cluster Based on Harris Hawks Optimization With an Adaptive Golden Sine Search Mechanism

Xie, Jiahao; Huang, Shucai; Wei, Daozhi; Zhang, Zhaoyu

doi:10.1109/jsen.2022.3164018

Cited by 7 publications

(3 citation statements)

References 33 publications

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“…In the formula, r 2 denotes a uniformly distributed random value in [0, 2π], r 3 denotes a uniformly distributed random value in [−2, 2], and r 4 denotes a uniformly distributed random value in [0, 1]. The calculation formula of r 1 is as follows [44]:…”

Section: Sine-cosine Algorithmmentioning

confidence: 99%

A Multi-Objective Optimization Problem Solving Method Based on Improved Golden Jackal Optimization Algorithm and Its Application

Jiang,

Yue,

Chen

et al. 2024

Biomimetics

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The traditional golden jackal optimization algorithm (GJO) has slow convergence speed, insufficient accuracy, and weakened optimization ability in the process of finding the optimal solution. At the same time, it is easy to fall into local extremes and other limitations. In this paper, a novel golden jackal optimization algorithm (SCMGJO) combining sine–cosine and Cauchy mutation is proposed. On one hand, tent mapping reverse learning is introduced in population initialization, and sine and cosine strategies are introduced in the update of prey positions, which enhances the global exploration ability of the algorithm. On the other hand, the introduction of Cauchy mutation for perturbation and update of the optimal solution effectively improves the algorithm’s ability to obtain the optimal solution. Through the optimization experiment of 23 benchmark test functions, the results show that the SCMGJO algorithm performs well in convergence speed and accuracy. In addition, the stretching/compression spring design problem, three-bar truss design problem, and unmanned aerial vehicle path planning problem are introduced for verification. The experimental results prove that the SCMGJO algorithm has superior performance compared with other intelligent optimization algorithms and verify its application ability in engineering applications.

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Section: Sine-cosine Algorithmmentioning

confidence: 99%

A Multi-Objective Optimization Problem Solving Method Based on Improved Golden Jackal Optimization Algorithm and Its Application

Jiang,

Yue,

Chen

et al. 2024

Biomimetics

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“…There are two technical schemes for processing industrial data at this stage. The first involves accessing industrial sites using embedded industrial gateways and collecting data through serial ports and servers [11][12][13]. The second scenario involves using a data terminal unit (DTU) to collect data and transfer them transparently to the cloud.…”

Section: Challengesmentioning

confidence: 99%

A Distributed Sensor System Based on Cloud-Edge-End Network for Industrial Internet of Things

Wang

Lin

et al. 2023

Future Internet

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The Industrial Internet of Things (IIoT) refers to the application of the IoT in the industrial field. The development of fifth-generation (5G) communication technology has accelerated the world’s entry into the era of the industrial revolution and has also promoted the overall optimization of the IIoT. In the IIoT environment, challenges such as complex operating conditions and diverse data transmission have become increasingly prominent. Therefore, studying how to collect and process a large amount of real-time data from various devices in a timely, efficient, and reasonable manner is a significant problem. To address these issues, we propose a three-level networking model based on distributed sensor self-networking and cloud server platforms for networking. This model can collect monitoring data for a variety of industrial scenarios that require data collection. It enables the processing and storage of key information in a timely manner, reduces data transmission and storage costs, and improves data transmission reliability and efficiency. Additionally, we have designed a feature fusion network to further enhance the amount of feature information and improve the accuracy of industrial data recognition. The system also includes data preprocessing and data visualization capabilities. Finally, we discuss how to further preprocess and visualize the collected dataset and provide a specific algorithm analysis process using a large manipulator dataset as an example.

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“… where and x * denotes the global optimal value. Many distributed optimization (DO) tasks in industry and economy can be transformed into Problem ( 1 ), such as sensor scheduling [ 1 , 2 ], robot fleeting [ 3 – 5 ], smart grid [ 6 , 7 ], etc. Thus problem ( 1 ) gained extensive research.…”

Section: Introductionmentioning

confidence: 99%

Distributed dynamic event-triggered algorithm for optimization problem with time delay

Jiang,

Xia,

Zhao

2024

PLoS ONE

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This paper focuses on studying the optimization problem of multi-agent systems (MAS) under undirected graph. To reduce the communication frequency among agents, a zero-gradient-sum (ZGS) algorithm based on dynamic event-triggered (DET) mechanism is investigated. The event-triggered condition of each agent only uses its own state information and the neighbor’s state information at the previous triggering instants, without requiring continuous state information from the neighbor. In addition, the designed algorithm allows for the sampling period to be arbitrarily large. The Lyapunov method is utilized to derive the sufficient conditions that incorporate time delay and parameters. As the event is only checked at the periodic moment, zeno behavior can be directly excluded. Finally, numerical simulations demonstrate the effectiveness of the theoretical results.

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Scheduling of Multisensor for UAV Cluster Based on Harris Hawks Optimization With an Adaptive Golden Sine Search Mechanism

Cited by 7 publications

References 33 publications

A Multi-Objective Optimization Problem Solving Method Based on Improved Golden Jackal Optimization Algorithm and Its Application

A Multi-Objective Optimization Problem Solving Method Based on Improved Golden Jackal Optimization Algorithm and Its Application

A Distributed Sensor System Based on Cloud-Edge-End Network for Industrial Internet of Things

Distributed dynamic event-triggered algorithm for optimization problem with time delay

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