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A novel distributed scheduling algorithm for maximizing total task allocations of multi-UAV systems.

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Title: A novel distributed scheduling algorithm for maximizing total task allocations of multi-UAV systems.
Authors: Yan, Shaokun1,2 (AUTHOR) yanshaokun@foxmail.com, Xia, Yuanqing1,3 (AUTHOR) xia_yuanqing@bit.edu.cn, Zhai, Dihua1 (AUTHOR) zhaidih@bit.edu.cn
Source: Journal of Supercomputing. Jul2025, Vol. 81 Issue 10, p1-31. 31p.
Subjects: Constraint algorithms, Distributed algorithms, Computational complexity, Algorithms, Mathematics
Abstract: This paper addresses the task allocation problem by maximizing the number of successfully allocated tasks through two decentralized algorithms: a novel performance impact algorithm with new scoring (PINS) and a local exchange performance impact algorithm (LEPI). PINS employs a scoring strategy that expands task inclusion capability in the task inclusion phase while ensuring tasks, once assigned, remain allocated. LEPI extends PINS by incorporating task reassignment to optimize allocations further. Evaluated in a deadline-limited and fuel-constrained simulated rescue scenario, both algorithms outperform existing methods and provably converge to conflict-free assignments within a finite number of iterations. Extensive simulations illustrate LEPI's superiority, improving the number of allocated tasks by up to 3.82% over the benchmarks; however, LEPI's substantially higher computational complexity limits its large-scale applicability. Conversely, PINS achieves up to 2.32% performance gains with computational complexity comparable to the Performance Impact (PI) algorithm. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Supercomputing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A novel distributed scheduling algorithm for maximizing total task allocations of multi-UAV systems.
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  Data: <searchLink fieldCode="AR" term="%22Yan%2C+Shaokun%22">Yan, Shaokun</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> yanshaokun@foxmail.com</i><br /><searchLink fieldCode="AR" term="%22Xia%2C+Yuanqing%22">Xia, Yuanqing</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<i> xia_yuanqing@bit.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhai%2C+Dihua%22">Zhai, Dihua</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zhaidih@bit.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Supercomputing%22">Journal of Supercomputing</searchLink>. Jul2025, Vol. 81 Issue 10, p1-31. 31p.
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  Label: Abstract
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  Data: This paper addresses the task allocation problem by maximizing the number of successfully allocated tasks through two decentralized algorithms: a novel performance impact algorithm with new scoring (PINS) and a local exchange performance impact algorithm (LEPI). PINS employs a scoring strategy that expands task inclusion capability in the task inclusion phase while ensuring tasks, once assigned, remain allocated. LEPI extends PINS by incorporating task reassignment to optimize allocations further. Evaluated in a deadline-limited and fuel-constrained simulated rescue scenario, both algorithms outperform existing methods and provably converge to conflict-free assignments within a finite number of iterations. Extensive simulations illustrate LEPI's superiority, improving the number of allocated tasks by up to 3.82% over the benchmarks; however, LEPI's substantially higher computational complexity limits its large-scale applicability. Conversely, PINS achieves up to 2.32% performance gains with computational complexity comparable to the Performance Impact (PI) algorithm. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Supercomputing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s11227-025-07598-9
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      – Code: eng
        Text: English
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        PageCount: 31
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    Subjects:
      – SubjectFull: Constraint algorithms
        Type: general
      – SubjectFull: Distributed algorithms
        Type: general
      – SubjectFull: Computational complexity
        Type: general
      – SubjectFull: Algorithms
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      – SubjectFull: Mathematics
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      – TitleFull: A novel distributed scheduling algorithm for maximizing total task allocations of multi-UAV systems.
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            NameFull: Yan, Shaokun
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            NameFull: Xia, Yuanqing
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              M: 07
              Text: Jul2025
              Type: published
              Y: 2025
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