Optimal Allocation of Human Resources Recommendation Based on Improved Particle Swarm Optimization Algorithm

People are the most dynamic factor of productivity, and human resource allocation is both the starting point and the end point of human resource management. In modern enterprises, human resource optimization is the scientific and rational allocation of human resources within the enterprise through c...

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Bibliographic Details
Published in:Mathematical problems in engineering 2022-08, Vol.2022, p.1-13
Main Author: Wei, Jintong
Format: Article
Language:English
Subjects:
Ant colony optimization
Efficiency
Employees
Employment
Evolutionary computation
Genetic algorithms
Human resource management
Optimization
Particle swarm optimization
Resource allocation
Swarm intelligence
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Summary:People are the most dynamic factor of productivity, and human resource allocation is both the starting point and the end point of human resource management. In modern enterprises, human resource optimization is the scientific and rational allocation of human resources within the enterprise through certain means and methods. The basic concept of particle swarm optimization (PSO) originates from the study of bird predation. It is an evolutionary computation technique based on the swarm intelligence method, which is similar to genetic algorithms and is a population-based optimization tool. This paper is inspired by the ant colony algorithm and introduces the ant colony pheromone and variation algorithm model into the PSO algorithm for further optimization. The application of this improved particle swarm optimization algorithm to the optimal allocation of human resources recommendations is demonstrated by a real case study.
ISSN:1024-123X
1563-5147
DOI:10.1155/2022/2010685