Research on Optimal Matching Scheme of Public Resource Management Based on the Computational Intelligence Model

The management of public resources means that people’s governments at all levels and other public administrative subjects should use certain means and methods, follow certain principles, rationally allocate and utilize public resources, and maximize their functions and benefits. Under the background...

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Veröffentlicht in:Scientific programming Jg. 2021; S. 1 - 10
Hauptverfasser: Li, Linna, Liu, Renjun
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Hindawi 18.11.2021
John Wiley & Sons, Inc
Schlagworte:
Ant colony optimization
Artificial intelligence
Assignment problem
Cloud computing
Decision making
Efficiency
Genetic algorithms
Human resources
Hydrology
Linear programming
Medical research
Multimedia communications
Neural networks
Optimization algorithms
Resource allocation
Resource management
Scheduling
ISSN:1058-9244, 1875-919X
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Zusammenfassung:The management of public resources means that people’s governments at all levels and other public administrative subjects should use certain means and methods, follow certain principles, rationally allocate and utilize public resources, and maximize their functions and benefits. Under the background of limited human resources, this study adheres to the principle of maximizing the benefits of human resources and rationally allocates the use of human resources. In this study, this kind of resource allocation problem is regarded as a linear programming problem by specifying the benefit function, and then, genetic algorithm, ant colony algorithm, and hybrid genetic-ant colony algorithm are used to solve the problem; the cost and time consumption of different algorithms under different scales are evaluated. Finally, it is found that genetic algorithm is superior to ant colony algorithm when the task scale is small and the effect of genetic algorithm is lower than ant colony algorithm with the expansion of task scale, whereas the improved hybrid genetic-ant colony algorithm is better than ordinary algorithm in general.
Bibliographie:ObjectType-Article-1
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ISSN:1058-9244
1875-919X
DOI:10.1155/2021/7960972