Multi-Task Scheduling Optimization Method Integrating Visibility Graph, Simulated Annealing, and A Algorithm

This paper presents a multi-task allocation method integrating the visibility graph, A* algorithm, and simulated annealing to enhance scheduling stability and path accuracy in complex environments. The method constructs a path cost matrix and globally optimizes task sequences. Experimental results s...

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Vydané v:	2025 2nd International Conference on Algorithms, Software Engineering and Network Security (ASENS) s. 263 - 267
Hlavní autori:	Luo, Guilan, Chen, Zijie, Zeng, Yongwang, Wang, Long, Wen, Shuzhen, Zhang, Mei
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 21.03.2025
Predmet:	A algorithm Accuracy Approximation algorithms ask allocation Costs Dynamic scheduling Heuristic algorithms Multitasking Path planning Resource management Simulated annealing Simulated annealing algorithm Software algorithms Visibility graph algorithm
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Shrnutí:	This paper presents a multi-task allocation method integrating the visibility graph, A* algorithm, and simulated annealing to enhance scheduling stability and path accuracy in complex environments. The method constructs a path cost matrix and globally optimizes task sequences. Experimental results show a 2% reduction in path length compared to Euclidean-based methods while improving path planning accuracy, allocation efficiency, and stability, providing a robust solution for dynamic multi-task scheduling.
DOI:	10.1109/ASENS64990.2025.11011007