基于改进布谷鸟算法的集装箱码头配载优化研究

Loading optimization for container terminal based on Improved Cuckoo Search algorithm

为对集装箱码头配载问题进行研究,在满足船舶适航性的基础上,建立了以集装箱水平运输时间、岸桥作业时间以及堆场倒箱时间最短为目标的多约束的数学模型。将改进的布谷鸟算法(Improved Cuckoo Search,ICS)应用求解,首先在布谷鸟算法的莱维飞行阶段,分别从种群整体、当代最优、自身个体中抽取鸟巢信息,建立不同的鸟巢位置更新模式;其次,采用动态机制控制发现概率P_(a);最后计算每个鸟巢的适应度,来找到最优解。试验表明:改进的布谷鸟算法可以有效找到最优解,优化结果相比较于标准的布谷鸟算法提升25%,该方法具有可行性和有效性。

A multi-constraint optimization model is built to minimize horizontal container transportation time,quay operation time and container dumping time in the yard under the condition of maintain the seaworthiness of the ship.The Improved Cuckoo Search algorithm is used to solve the problem.The nest information is extracted from the population as a whole,the contemporary optimal solution and its own individuals in the Levi flight stage and a variety of location updating modes are established.The discovery probability P_(a)is controlled by dynamic mechanism.The optimal solution is found by calculating the fitness function value of each net.Experiments are carried out with a typical data set.For the cited data,the optimization result is 25% higher than that produced by conventional cuckoo algorithm.Which proves the feasibility and effectiveness of the method.