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

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...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:IEEE transactions on intelligent transportation systems Ročník 23; číslo 8; s. 13040 - 13054
Hlavní autori: Huang, Haiping, Hu, Chengxi, Zhu, Jie, Wu, Min, Malekian, Reza
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.08.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Costs
Heuristic algorithms
Heuristics algorithm
Logistics
Multitasking
O2O on-demand meal delivery
On demands
Random processes
rescheduling strategy
Routing
Routing algorithms
Routings
Scheduling algorithms
Simulated annealing
Stochastic processes
Stochastic systems
Stochastic task
stochastic task scheduling
Stochastics
Task analysis
Task scheduling
UAV
Unmanned aerial vehicles (UAV)
Vehicle dynamics
Vehicle's dynamics
ISSN:1524-9050, 1558-0016, 1558-0016
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí: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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1524-9050
1558-0016
1558-0016
DOI:10.1109/TITS.2021.3119343