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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Hindawi Limited
2021
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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) |
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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 |
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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 |
_version_ |
1718407779380625408 |