Stochastic Task Scheduling in UAV-Based Intelligent On-Demand Meal Delivery System.

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Název: Stochastic Task Scheduling in UAV-Based Intelligent On-Demand Meal Delivery System.
Autoři: Huang, Haiping, Hu, Chengxi, Zhu, Jie, Wu, Min, Malekian, Reza
Zdroj: IEEE Transactions on Intelligent Transportation Systems; Aug2022, Vol. 23 Issue 8, p13040-13054, 15p
Abstrakt: In this paper, we investigate the dynamic task scheduling problem with stochastic task arrival times and due dates in the UAV-based intelligent on-demand meal delivery system (UIOMDS) to improve the efficiency. The objective is to minimize the total tardiness. The new constraints and characteristics introduced by UAVs in the problem model are fully studied. An iterated heuristic framework SES (Stochastic Event Scheduling) is proposed to periodically schedule tasks, which consists of a task collection and a dynamic task scheduling phases. Two task collection strategies are introduced and three Roulette-based flight dispatching approaches are employed. A simulated annealing based local search method is integrated to optimize the solutions. The experimental results show that the proposed algorithm is robust and more effective compared with other two existing algorithms. [ABSTRACT FROM AUTHOR]
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Databáze: Complementary Index
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Abstrakt:In this paper, we investigate the dynamic task scheduling problem with stochastic task arrival times and due dates in the UAV-based intelligent on-demand meal delivery system (UIOMDS) to improve the efficiency. The objective is to minimize the total tardiness. The new constraints and characteristics introduced by UAVs in the problem model are fully studied. An iterated heuristic framework SES (Stochastic Event Scheduling) is proposed to periodically schedule tasks, which consists of a task collection and a dynamic task scheduling phases. Two task collection strategies are introduced and three Roulette-based flight dispatching approaches are employed. A simulated annealing based local search method is integrated to optimize the solutions. The experimental results show that the proposed algorithm is robust and more effective compared with other two existing algorithms. [ABSTRACT FROM AUTHOR]
ISSN:15249050
DOI:10.1109/TITS.2021.3119343