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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Autores principales: Linna Li, Renjun Liu
Formato: article
Lenguaje:EN
Publicado: Hindawi Limited 2021
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Acceso en línea:https://doaj.org/article/7e7630a5aa0e49d688993fed6028d157
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spelling oai:doaj.org-article:7e7630a5aa0e49d688993fed6028d1572021-11-29T00:55:36ZResearch on Optimal Matching Scheme of Public Resource Management Based on the Computational Intelligence Model1875-919X10.1155/2021/7960972https://doaj.org/article/7e7630a5aa0e49d688993fed6028d1572021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/7960972https://doaj.org/toc/1875-919XThe 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.Linna LiRenjun LiuHindawi LimitedarticleComputer softwareQA76.75-76.765ENScientific Programming, Vol 2021 (2021)
institution DOAJ
collection DOAJ
language EN
topic Computer software
QA76.75-76.765
spellingShingle Computer software
QA76.75-76.765
Linna Li
Renjun Liu
Research on Optimal Matching Scheme of Public Resource Management Based on the Computational Intelligence Model
description 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.
format article
author Linna Li
Renjun Liu
author_facet Linna Li
Renjun Liu
author_sort Linna Li
title Research on Optimal Matching Scheme of Public Resource Management Based on the Computational Intelligence Model
title_short Research on Optimal Matching Scheme of Public Resource Management Based on the Computational Intelligence Model
title_full Research on Optimal Matching Scheme of Public Resource Management Based on the Computational Intelligence Model
title_fullStr Research on Optimal Matching Scheme of Public Resource Management Based on the Computational Intelligence Model
title_full_unstemmed Research on Optimal Matching Scheme of Public Resource Management Based on the Computational Intelligence Model
title_sort research on optimal matching scheme of public resource management based on the computational intelligence model
publisher Hindawi Limited
publishDate 2021
url https://doaj.org/article/7e7630a5aa0e49d688993fed6028d157
work_keys_str_mv AT linnali researchonoptimalmatchingschemeofpublicresourcemanagementbasedonthecomputationalintelligencemodel
AT renjunliu researchonoptimalmatchingschemeofpublicresourcemanagementbasedonthecomputationalintelligencemodel
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