航班延误恢复调度的混合粒子群算法

为了优化航班延误恢复调度, 考虑了航班延误的经济效益、社会影响和经济损失构成, 定义了航线影响因子, 构建了一种新的航班延误恢复调度模型, 将局部搜索方法引入到粒子群算法中, 提出了求解航班延误恢复调度问题的混合粒子群算法。计算结果表明: 与先来先服务调度方法相比, 混合粒子群算法可以减少航班延误损失4.2%, 与基本粒子群算法和进化策略算法相比, 混合粒子群算法平均可减少航班延误损失2.0%, 随着航班延误恢复规模的增大, 算法优势会更明显。

Hybrid particle swarm optimization arithmetic for recovery scheduling of flight delays

In order to optimize the recovery scheduling of flight delays,airline impact factors were defined,the economic benefit,social impact and loss constitution of flight delays were considered,a new recovery scheduling model of flight delays was created,a hybrid particle swarm optimization arithmetic(HPSOA)was put forward,and local search method was introduced into the arithmetic.Computation result shows that HPSOA can reduce the flight delay losses by 4.2% compared with first-come-first-serve(FCFS)strategy,and evenly reduce the flight delay losses by 2.0% compared with basic PSOA and evolutionary strategy(ES),so the advantage of HPSOA is more obvious with the increase of recovery scale in flight delays.8 tabs,3 figs,10 refs.