摘要
探索了群智能算法的混合并加入模糊集理论来尝试解决工程优化问题.将HGAPSO算法应用在工程实践的实际案例中,并与其他算法运算结果进行了对比.结果表明,在本文中的两个实际案例中的TCRO问题里,HGAPSO算法能够更好地找出问题的最优解.
Project progress control is one of the three major controls in the current project management—quality control,progress control and cost control.The progress control generally adopts network planning technology.In the technical problems of network planning,scientists usually use the theory of“minimum cut set”,charting method and other methods to deal with the problem of duration optimization.In recent years,swarm intelligence algorithms have been widely used in network planning problems in construction projects,such as taboo search method(TS),simulated annealing method(SA),particle group algorithm(PSO),and genetic algorithm(GA).In this paper,the HGAPSO algorithm is applied in the practical case of engineering practice,and the results are compared with those of other algorithms,and the results show that in the TCRO problem in the two practical cases in this paper,the HGAPSO algorithm can find out the better solution for the problems.
作者
李波
王妍
LI Bo;WANG Yan(School of Computer Technology and Engineering,Changchun Institute of Technology,Changchun 130012,China)
出处
《东北师大学报(自然科学版)》
CAS
北大核心
2021年第4期54-61,共8页
Journal of Northeast Normal University(Natural Science Edition)
基金
吉林省自然科学基金资助项目(2018010107JC)
吉林省科技发展技术攻关项目(20190302110GX)
长春工程学院青年基金资助项目(320190015).
关键词
群智能算法
GA
PSO
swarm intelligence algorithms
GA
PSO