An Energy-Efficient Thrust Allocation Based on the Improved Dung Beetle Optimizer for the Dynamic Positioning System of Vessels

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Publicado no:Journal of Marine Science and Engineering vol. 13, no. 6 (2025), p. 1041-1060
Autor principal: Tuo Yulong
Outros Autores: Lin, Jianlong, Peng Zhouhua, Wang, Yuanhui, Wang, Shasha
Publicado em:
MDPI AG
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100 1 |a Tuo Yulong  |u College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China; tuoyulong@dlmu.edu.cn (Y.T.); linjianlong@dlmu.edu.cn (J.L.) 
245 1 |a An Energy-Efficient Thrust Allocation Based on the Improved Dung Beetle Optimizer for the Dynamic Positioning System of Vessels 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a This paper investigates the constrained nonlinear thrust allocation problem for the dynamic positioning system of vessels. Considering the wear, energy consumption, and allocation error of thrusters, a constrained nonlinear mathematical optimization model of thrust allocation is established based on the “Hai Yang Shi You 201”. Based on the dung beetle optimizer (DBO) algorithm, a hybrid Osprey adaptive t-distribution DBO (HOATDBO) algorithm is presented to achieve the thrust allocation. The HOATDBO algorithm introduces the global exploration strategy of the Osprey algorithm, with the addition of the initialization of the good point set and adaptive t-distribution perturbations. The proposed HOATDBO algorithm has perfect global and local optimization capabilities, which can quickly and reliably obtain the optimal thrust solution, improve the thrust allocation accuracy of vessels, and reduce energy consumption. Finally, the simulation and comparison results are presented to verify the superiority of the proposed HOATDBO algorithm. 
653 |a Accuracy 
653 |a Mathematical analysis 
653 |a Algorithms 
653 |a Beetles 
653 |a Energy efficiency 
653 |a Thrusters 
653 |a Dung 
653 |a Vessels 
653 |a Foraging behavior 
653 |a Energy consumption 
653 |a Optimization models 
653 |a Machine learning 
653 |a Positioning systems 
653 |a Dynamic positioning 
653 |a Energy 
653 |a Local optimization 
653 |a Constraints 
653 |a Optimization algorithms 
653 |a Probability distribution 
653 |a Economic 
700 1 |a Lin, Jianlong  |u College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China; tuoyulong@dlmu.edu.cn (Y.T.); linjianlong@dlmu.edu.cn (J.L.) 
700 1 |a Peng Zhouhua  |u College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China; tuoyulong@dlmu.edu.cn (Y.T.); linjianlong@dlmu.edu.cn (J.L.) 
700 1 |a Wang, Yuanhui  |u College of Intelligent System Science and Engineering, Harbin Engineering University, Harbin 150001, China; wangyuanhui@hrbeu.edu.cn 
700 1 |a Wang, Shasha  |u College of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China; tuoyulong@dlmu.edu.cn (Y.T.); linjianlong@dlmu.edu.cn (J.L.) 
773 0 |t Journal of Marine Science and Engineering  |g vol. 13, no. 6 (2025), p. 1041-1060 
786 0 |d ProQuest  |t Engineering Database 
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