进港飞机调度多目标优化问题的改进NSGA-II算法

Improved Nondominated Sorting Genetic Algorithm II for Multi-Objective Optimization of Scheduling Arrival Aircrafts

基于多目标优化问题的Pareto最优解概念,提出了一种求解非劣解集的改进非支配排序遗传算法(NSGA-II),用于解决多条跑道情况下进港航班调度问题,要求航班总延误时间平方和及总延误成本两个目标最少。重点讨论了算法实现中的基于最近邻思想的启发式交叉算子和改进的变异算子,以及对非劣解集的筛选操作。最后进行了仿真实验,对优化结果进行了分析比较。研究结果表明改进NSGA-II算法对多跑道进港飞机调度多目标优化问题具有较好的应用前景。

Based on the Pareto optimal conception,an Improved nondominated sorting genetic algorithm II （NSGA-II） seeking non-inferior solution set of multi-objective optimization （MO） problems is proposed, while the heuristic crossover operator based on nearest-neighborhood, the improved mutation operator and the filtering of non-inferior solutions are focused and discussed. The algorithm proposed is applied to a two-objective optimization of scheduling of arrival aircrafts at an airport with multiple runways, where both the sum of all the delays squared and the fuel cost of all the aircrafts were required to be minimized. After the simulation experiment, the optimal solutions are analyzed and compared with the best solutions founded by some existing algorithms. The research result demonstrates that improved NSGA-II possesses a good application foreground for multi-objective optimization of scheduling arrival aircrafts at an airport with multiple runways.