Design and Application of Vague Set Theory and Adaptive Grid Particle Swarm Optimization Algorithm in Resource Scheduling Optimization Design and Application of Vague Set Theory and Adaptive Grid Particle Swarm Optimization Algorithm in Resource Scheduling Optimization

The purpose of resource scheduling is to deal with all kinds of unexpected events that may occur in life, such as fire, traffic jam, earthquake and other emergencies, and the scheduling algorithm is one of the key factors affecting the intelligent scheduling system. In the traditional resource sched...

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Vydané v:Journal of grid computing Ročník 21; číslo 2; s. 24
Hlavní autori: Han, Yibo, Han, Pu, Yuan, Bo, Zhang, Zheng, Liu, Lu, Panneerselvam, John
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Dordrecht Springer Netherlands 01.06.2023
Springer Nature B.V
Predmet:
Algorithms
Computer Science
Decision making
Emergencies
Management of Computing and Information Systems
Multiple objective analysis
Optimization algorithms
Particle swarm optimization
Processor Architectures
Resource allocation
Resource scheduling
Scheduling
Set theory
Traffic congestion
Traffic jams
User Interfaces and Human Computer Interaction
Vague set theory
Model
Multi objective
Resource scheduling
Particle swarm optimization algorithm
ISSN:1570-7873, 1572-9184, 1572-9184
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Shrnutí:The purpose of resource scheduling is to deal with all kinds of unexpected events that may occur in life, such as fire, traffic jam, earthquake and other emergencies, and the scheduling algorithm is one of the key factors affecting the intelligent scheduling system. In the traditional resource scheduling system, because of the slow decision-making, it is difficult to meet the needs of the actual situation, especially in the face of emergencies, the traditional resource scheduling methods have great disadvantages. In order to solve the above problems, this paper takes emergency resource scheduling, a prominent scheduling problem, as an example. Based on Vague set theory and adaptive grid particle swarm optimization algorithm, a multi-objective emergency resource scheduling model is constructed under different conditions. This model can not only integrate the advantages of Vague set theory in dealing with uncertain problems, but also retain the advantages of adaptive grid particle swarm optimization that can solve multi-objective optimization problems and can quickly converge. The research results show that compared with the traditional resource scheduling optimization algorithm, the emergency resource scheduling model has higher resolution accuracy, more reasonable resource allocation, higher efficiency and faster speed in dealing with emergency events than the traditional resource scheduling model. Compared with the conventional fuzzy theory emergency resource scheduling model, its handling speed has increased by more than 3.82 times.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1570-7873
1572-9184
1572-9184
DOI:10.1007/s10723-023-09660-3