考虑学习效应的复杂工程网络优化及仿真
Task Flow Optimization and Risk Simulation Model of Complex Construction Proje
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摘要: 为了有效管理和控制复杂工程项目的成本和进度,文章提出了一种项目网络流程优化算法。 该优化算法以设计结构矩阵为基本分析工具,通过重新安排任务的执行顺序,降低项目执行 过程中的返工迭代来优化整个项目的工期和费用。考虑到项目执行过程中部分任务需要返工 多次才能满足要求,着重考虑了学习效用对于项目时间和费用的影响。算例仿真结果表明, 项目中的学习效应会对成本和进度产生显著影响,对于任务之间存在具有高度耦合关系的复 杂工程项目,该优化算法可以有效地降低项目执行成本和执行费用。Abstract: In order to effectively manage the schedule and cost of complex construction pro jects, an algorithm is developed to optimize task flows. This algorithms uses De sign Structuring Matrix as the basic analysis tool, and optimizes the task flow through reorganizing the tasks execution sequence. As learning curve will play a n important role in the completion of complex project, this paper also takes thi s factor into consideration. The simulation results in the case study indicates that it is quite effective for projects with high task interactions, and the lea rning curve will pose a significant effect upon project cost and schedule.