期刊论文

中文

计算机应用研究

1001-3695

2015

32

7

2035-2038

10.3969/j.issn.1001-3695.2015.07.029

本校为第一机构

航班降落调度是多约束的整数规划问题,也是组合优化中的典型NP难题之一。针对传统粒子群算法易陷入局部最优和求解组合优化问题能力不强的缺点,提出改进策略。改进的算法通过禁忌搜索策略生成初始粒子群以满足航班调度多约束的限制,引入遗传算法的交叉变异等操作以增强粒子群间信息交流能力,重新定义惯性权重和加速度因子,以增强粒子的多样性和收敛性,加入进化交叉算子以增强粒子的局部寻优能力。通过与修补遗传算法、罚函数遗传算法进行对比,经多次运行后的结果表明,提出的改进算法的局部搜索能力和全局搜索能力都得到增强,同时也验证了算法的可行性和有效性。

Flight landing scheduling was a more constrained integer programming problem. It was also one of the typical NP problems in combinatorial optimization. In view of the problem that traditional particle swarm optimization （PSO） algorithm was easy to fall into local optimum and the ability of combinatorial optimization problem was not strong, it proposed the improved strategies. The improved algorithm generated the initial particle swarm to satisfy the constraint of flight scheduling constraints through the tabu search strategy. And it introduce...