An enhanced dung beetle optimizer with adaptive node selection and dynamic step search for mobile robots path planning

Measurement Science and Technology, Год журнала: 2025, Номер 36(3), С. 036301 - 036301

Опубликована: Янв. 20, 2025

Abstract Path planning plays a crucial role in determining the shortest and safest route for autonomous mobile robots, metaheuristic optimization algorithms have demonstrated their efficacy solving complex problems involving numerous variably shaped obstacles. The dung beetle optimizer (DBO) emerges as novel heuristic algorithm, drawing inspiration from behavior patterns exhibited by beetles. This paper presents an improved algorithm called enhanced DBO (EDBO) designed to address robot path problem. First, node selection strategy based on search radius is proposed reduce probability of reciprocation while concurrently enhancing initial population quality. Second, conventional ball-rolling employed replaced with dynamic step size strategy. dynamically adjusts relative distance between current position worst each iteration, enabling update its adaptively response environmental changes. Additionally, global optimal incorporated guide process, thereby improving performance DBO. Finally, fine-tuning implemented refine new generated individuals, geometric principles triangles being introduced locally adjust optimized out local optima. Experiments are conducted validate effectiveness three improvement strategies, comparing EDBO five other across different complexity environments. two statistical testing methods evaluate experimental results. results indicate that, all environments, outperforms terms length achieves superior smoothness 80% cases. Moreover, consistently demonstrates better overall than DBO, excelling both convergence accuracy speed.

Язык: Английский

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Multi-resource constrained elective surgical scheduling with Nash equilibrium toward smart hospitals

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Янв. 31, 2025

This paper focuses on the elective surgical scheduling problem with multi-resource constraints, including material resources, such as operating rooms (ORs) and non-operating room (NOR) beds, human resources (i.e., surgeons, anesthesiologists, nurses). The objective of constrained (MESS) is to simultaneously minimize average recovery completion time for all patients, overtime medical staffs, total cost. can be formulated a mixed integer linear multi-objective optimization model, honey badger algorithm based Nash equilibrium (HBA-NE) developed MESS. Experimental studies were carried out test performance proposed approach, scheme was validated. Finally, narrow gap between optimal solution actual hospital operations, digital twin (DT) technology adopted build physical-virtual surgery simulation model. experimental results show that by introducing twin, physical virtual spaces smart integrated visually simulate verify processes.

Язык: Английский

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A novel marine predator algorithm for path planning of UAVs

The Journal of Supercomputing, Год журнала: 2025, Номер 81(4)

Опубликована: Фев. 18, 2025

Язык: Английский

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Hybrid attacks collaborative defense model using an ensemble Honey Badger Algorithm

Computer Networks, Год журнала: 2025, Номер unknown, С. 111149 - 111149

Опубликована: Фев. 1, 2025

Язык: Английский

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500 KV Transmission Tower Drone Inspection Path Planning Approach Based on Honey Badger Optimization Algorithm

Lecture notes in electrical engineering, Год журнала: 2025, Номер unknown, С. 303 - 313

Опубликована: Янв. 1, 2025

Язык: Английский

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