飞机着陆调度优化的混合免疫克隆算法

HYBRID IMMUNE CLONAL ALGORITHM FOR AIRCRAFT LANDING SCHEDULING OPTIMISATION

飞机着陆调度是一个多约束NP难的组合优化问题。设计一种混合免疫克隆算法,采用双实数链编码,通过幅度角旋转同步更新,保持种群多样性;利用启发式变异算子进行广度寻优,得到较优秀的飞机序列;为加速深度探索,提出一种高效的确定性算法帮助优化飞机的实际降落时间。实验表明,在静态以及动态不同的问题背景下,该算法都可以在极短的时间内得到最优解,具有较好的全局寻优能力和较快的收敛速度。

Aircraft landing scheduling is a NP-hard multi-constrained combinatorial optimisation problem.A hybrid immune clonal algorithm is designed,which adopts double real-number chains coding,and keeps synchronous update through the rotation of the margin angle to maintain the diversity of population.Excellent aircraft landing sequence can be obtained by breadth optimisation using heuristic mutation operator.In order to accelerate the exploration in depth,a highly efficient deterministic algorithm is proposed to optimise practical landing time of the aircrafts.Experimental results based on static and dynamic cases show that this algorithm is able to attain the optimal solution in extremely short time and has the capability of global optimisation and fast convergence speed.