基于微粒群算法的工程网络计划多资源均衡优化研究  

Multi-resources Leveling Optimization in Project Network Planning Based on PSO Algorithm

作　　者：刘迅[1] 毕远志[1] 

机构地区：[1]江南大学工程管理系,江苏无锡214122

出　　处：《科技管理研究》2014年第11期182-187,共6页Science and Technology Management Research

基　　金：江南大学青年基金项目"基于贝叶斯网络推理的工程项目进度和费用风险预测与控制模型"(JUSRP1031)

摘　　要：为了更有效地解决工程施工管理中的多资源均衡问题,将改进的微粒群算法应用到多资源均衡优化中来,利用微粒群算法原理中粒子飞行中位置的进化过程来搜索各工序活动的最优开始时间方案。通过算例证明,该设计的目标函数可以更好地反映多资源均衡程度,同时以粒子群算法来解决此类问题具有搜索精度高,计算结果较为理想,贴近实际的特点,反映了在工程项目管理的多资源均衡优化中的可行性及有效性。文章提出的算法对于工程网络计划中的多资源均衡优化具有实际应用价值。This paper designed a multi - objective function of resource leveling and created the multi - resources leveling model on the basis of particle swarm optimization algorithm. The model combines multi - resources leveling in project net- work planning with particle swarm optimization algorithm, and searches for the position corresponding to the optimal solution activity actual start time through the flight during the evolutionary process. The objective function can better reflect the de- gree of multi - resources leveling by an example. Also the paper found that the particle swarm algorithm has characteristics Of high precision, more ideal calculation and close to the actual. The results reflect the feasibility and effectiveness in the multi - resources leveling for project management. The proposed algorithm is valuable in practical application for the multi -resource leveling optimization in engineering project management.

关 键 词：37-程网络计划 多资源均衡 粒子群算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]