基于微粒群算法的工程项目资源均衡优化

将微粒群算法运用到工程项目管理的资源均衡优化问题,定义了以活动的实际开始时间作为微粒坐标的微粒群;建立了资源方差与活动实际开始时间直接联系的评价函数;通过微粒群在飞行中位置的进化过程来搜索对应于最优方案的活动实际开始时间。最后通过算例的计算分析,用微粒群算法得到的资源强度比初始方案降低了75.2%,比遗传算法的结果降低了26.97%,验证了该方法在工程项目管理的资源均衡优化中的可行性及有效性,同时还获得了若干个次优方案,对于工程项目管理中的资源均衡优化具有实际应用价值。

Research on the unlimited resource leveling optimization with PSO

The PSO(particle swarm optimization) was applied for the unlimited resource leveling optimization of construction engineering in this paper.Defined the particle swarm whose coordinates were used for the activity's actual start time.Established the appraisal function between the resource variance and the activity's actual start time.Searched the best schedule of project by the evolution of the particle swarm's position during its flying.Finally,the resource intensity obtained by PSO reduced 75.2% compared to the initial schedule,reduced 26.97% compared to the GA's(genetic algorithm) result according to the case analysis.Validated the feasibility and the effectivity of the PSO in the unlimited resource leveling optimization,and also obtained several secondary optimum schedules as well as the best one.Therefore,this method has its practical application value for the resource leveling optimization.