机场地勤服务优化问题的双重变异单亲遗传算法

为了减少地勤服务作业调度影响的航班延误，以总航班延误最小化及航班延误方差最小化为目标建立了多目标非线性整数优化模型.地勤服务作业调度优化问题是NP难问题，因此，提出了一种双重变异单亲遗传算法求解该类问题.该算法避免了遗传算法求解同类问题时产生非法个体的现象，并且双重变异策略具有全局搜索能力.结果表明:双重变异单亲遗传算法可以很好地解决航班分配服务组及服务组内航班服务序列优化的地勤服务调度问题，减少了因地勤服务作业导致的航班总延误，避免了单个航班长时间延误.

Double-Mutation Partheno-Genetic Algorithm for Airport Ground Service Optimization

In order to reduce the flight delays caused by airport ground service task scheduling， a multi-objective nonlinear integer optimization model was established to minimize total flight delays and flight delay variance. Ground service task scheduling optimization is an NP-hard problem， so， a double-mutation partheno-genetic algorithm was proposed to solve this problem. The algorithm avoids the phenomenon that the genetic algorithm generates illegal individuals when solving similar problems， and the double-mutation strategy has global search capability. The simulation result showed that the double-mutation partheno-genetic algorithm can solve the ground service scheduling optimization problem including assignment of service teams to airlines and airline-service sequence optimization inside a service team， reduce the total flight delays caused by ground service tasks and avoid long single-flight delay.