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September 18, 2025VehiclesOpen Access

Multi-AGV Scheduling and Path Planning Based on an Improved Ant Colony Algorithm

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The improved ant colony algorithm significantly reduces task completion time in multi-AGV systems, enhancing operational performance.
Results demonstrate improvements in scheduling efficiency and overall task allocation, leading to reduced idle travel distances.
By integrating shortest-path planning with task execution capabilities, the model effectively optimizes both task allocation and path planning.
The findings highlight the algorithm’s feasibility for real-world applications in intelligent manufacturing environments.

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Analysis reveals enhanced scheduling efficiency and task allocation in multi-AGV systems, indicating better path planning solutions.

Xu et al. (2025) studied this question.

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