Practice System of Ant Colony Optimization Algorithm in Business Administration

被引:0
|
作者
Ma, Deyong [1 ]
Wang, Jun [1 ]
机构
[1] Hainan Univ, Haikou, Hainan, Peoples R China
关键词
Ant Colony Optimization Algorithm; Particle Swarm Optimization; Business Administration; Market Regulation;
D O I
10.1007/978-981-19-7842-5_15
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
AS a result of routine businessmanagement in the practical application of such problems as low efficiency, the content is not fine, so if you want to optimize the effect of market regulation, improve business management efficiency, and ensure quality of market operation, need to be in the original content on the basis of reasonable use of information technology management idea, this is also discusses the main problems of the current market industry. Based on the application of particle swarm optimization (PSO), this paper integrates it with ant colony algorithm, and then uses the whole process of fine management mode to carry out visual and cyclic supervision and scheduling of the whole market inspection process. The results of this study can improve actual work efficiency, strengthen industrial and commercial scheduling management, and reduce the work pressure faced by industrial and commercial personnel. It is thework content of enterprise management that is more standardized.
引用
收藏
页码:159 / 168
页数:10
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