基于自适应多局部搜索memetic算法的多跑道地面等待问题求解

建立了一种综合考虑航班延误成本差别、续航航班延误时间的单机场地面等待问题优化模型, 对独立运行的多条跑道进行合理、有效分配, 满足大型繁忙机场的运营需求; 然后提出了一种自适应多局部搜索memetic算法来加以求解. 鉴于问题模型的复杂性以及单一局部搜索memetic算法对复杂问题显露出的较弱的寻优能力和收敛性, 提出的自适应多局部搜索memetic算法在不同阶段采用不同的局部搜索策略, 其中自适应定向局部搜索策略使个体的搜索速度根据个体、最优个体以及群体信息进行调整. 通过对多组仿真算例进行计算, 并与其它典型算法的求解结果进行对比, 实验结果表明了所提模型与算法的有效性.

Solution to multi-runway ground-holding problem based on adaptive multi-local search memetic algorithm

Firstly, an optimization model was proposed for single airports ground-holding problem, in which the factors concerning the different delay costs of different planes and delay time of flights with continuation of the journeys. Moreover, the proposed model can reasonably and effectively assign multiple independently-running runways to meet the operating demand of large busy airports. Then an adaptive multi-local search memetic algorithm was designed to solve this model. In view of complexity of the model, poor convergence and optimizing ability that single local search memetic algorithm manifests when solving complicated problem, different local search strategies were used at different stages in proposed adaptive multi-local search memetic algorithm, among them adaptive directed local search strategy adjusted individual searching speed according to messages of the individual, best individual and population. Finally the simulation was implemented with the data in many examples, experimental results show that, compared with the results of other representative algorithms, the validity of the proposed algorithm and model.