微粒群算法在工程项目资源均衡优化中的应用

The Application of PSO in Unlimited Resource Leveling Optimization

在工程项目管理的资源优化中应用微粒群算法,定义了微粒坐标是活动的实际开始时间的微粒群;建立了一个直接反映资源强度与活动实际开始时间之间关系的评价函数;以微粒群算法为基础,编码设计搜索最佳方案的活动实际开始时间。最后计算分析典型算例,初始方案结果比微粒群算法得到的结果高出3倍多,遗传算法的结果比微粒群算法的结果高出53.52%,由此证明了微粒群算法在工程项目管理的资源均衡优化中的可行性及有效性。

In this paper,when dealing with the unlimited resource leveling optimization of engineering,the PSO was applied.The particle swarm optimization whose coordinates were the actual start time of the activity was defined.Established anevaluation function who was able to reflect the relationship between the resource intensity and the actual start time of the activity directly.Based on the particle swarm optimization,searched the activity＇s actual start time of the best program by code design.Finally,the resource intensity obtained by initial program was more than three times higher than the particle swarm,the result of the genetic algorithm was 53.52% higher than the swarm algorithm according to the case analysis.Thusproving the feasibility and effectiveness of PSO in the unlimited resource leveling optimization.