面向拥堵问题的枢纽航线网络优化模型

为解决枢纽机场客流拥堵问题,提高机场运行效率,减少运营成本,提出了一种面向拥堵问题的枢纽航线网络优化模型。该模型基于非严格枢纽航线网络结构,以不同运输方式的费用和流量为约束条件,以枢纽航线网络成本最低为目标，设计了能够减少求解运算的复杂变量表示方法,以及减少陷入局部最优解概率的模拟退火粒子群优化(simulated annealing particle swarm optimization, SAPSO)算法。实验结果表明,相较于严格的枢纽航线网络,所提优化模型能够显著地缓解枢纽机场的拥堵,均衡枢纽机场间客流量,减少网络成本;同时,所提算法具有较快的收敛速度和良好的稳定性。

Optimization model of hub-and-spoke network for congestion problem

In order to solve the problem of passenger flow congestion at the hub airport, improve airport operation efficiency, and reduce operating costs, an optimization model of the hub-and-spoke network for congestion problem is proposed. The model is based on the structure of non-strict hub-and-spoke network, with costs and flows of different modes of transportation as constraints, and the goal of minimizing the hub-and-spoke network costs. A complex variable representation method that can reduce the calculation and the simulated annealing particle swarm optimization (SAPSO) algorithm, which can reduce the probability of falling into a local optimal solution is designed. The experimental results show that compared with the strict hub-and-spoke network, the optimization model proposed can significantly alleviate the congestion of the hub airport, balance passnger flow between hub airports and reduce the network cost. At the same time, the proposed algorithm has faster convergence speed and better stability.