Research on Optimal Matching Scheme of Public Resource Management Based on the Computational Intelligence Model
| Autor: | Linna Li, Renjun Liu |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Mathematical optimization
Optimal matching Article Subject Linear programming Computer science Ant colony optimization algorithms media_common.quotation_subject Computational intelligence ComputingMethodologies_ARTIFICIALINTELLIGENCE Computer Science Applications Task (project management) QA76.75-76.765 Genetic algorithm Resource allocation Computer software Function (engineering) Software media_common |
| Zdroj: | Scientific Programming, Vol 2021 (2021) |
| ISSN: | 1875-919X 1058-9244 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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