摘要
为了控制项目实施过程中的风险,提高项目的成功率,针对项目实施过程中时间、成本、质量的不确定优化问题,结合PERT技术分别提出了基于机会约束规划的项目关键路线实施进度优化模型、项目实施进度—费用优化模型、项目实施质量优化模型和项目进度—费用—质量联合折衷优化模型,并采用随机模拟技术通过Monte Carlo仿真给出了项目实施风险的概率估计.利用嵌入PERT的基于随机模拟的遗传算法对模型求解,通过算例验证了模型的合理性和算法的有效性,根据对比,进度—费用—质量联合折衷模型的解方案具有更小的实施风险概率,为项目实施方案规划提供了定量可靠的决策依据.
To control the risks in project implementation and raise the success rate of projects, we proposed four optimization models for solving the indefinite optimization problems of time, cost and quality in project implementation by using program evaluation and review technique （PERT） and chance-constrained programming. These models include a project implementation progress optimization model based on critical path, a time/cost trade-off optimization model, an implementation quality optimization model, and a schedule-cost-quality compromise optimization model. Then, a project implementation risk probability estimation was carried out using Monte Carlo simulation. The models were solved With genetic algorithm embedded in PERT. The practical examples verify the correctness of these models and effectiveness of the related algorithms. The comparison between these models showed that, the schedule-cost-quality compromise optimization model possesses lowest probability of implementation risk, providing the quantitative and authentic decision-making basis for planning of project implementation schemes.
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2008年第6期610-616,共7页
Journal of Harbin Engineering University
基金
国家863/CIMS主题基金资助项目(2003AA413210)
关键词
项目优化
机会约束规划
计划评审技术
遗传算法
project optimization
chance-constrained programming
PERT
genetic algorithm
