一种新的集卡动态调度模型及算法  

Dynamic Dispatch Model of Container Trucks Based on Hybrid Genetic Algorithm

作　　者：李尤丰[1] 李勤丰[2,3] 刘玉霞[4] 周晓峰[3] 

机构地区：[1]金陵科技学院信息技术学院,江苏南京211169 [2]金陵科技学院公共基础课部,江苏南京211169 [3]河海大学计算机与信息学院,江苏南京211100 [4]解放军国际关系学院基础部,江苏南京210039

出　　处：《南京师大学报（自然科学版）》2014年第1期104-111,共8页Journal of Nanjing Normal University(Natural Science Edition)

基　　金：江苏省现代教育技术研究课题(2011-R-19470)

摘　　要：港口物流环节中,集卡的调度直接影响着港口的工作效率.目前,对集卡装和卸同时进行的调度模型和算法鲜有研究.本文以一艘船待装集装箱、一艘船待卸集装箱、装卸同时进行为例,提出一种动态优化模型,并用遗传算法求解.但其不同于一般的遗传算法,这里创造性地引入N6邻域方法来减少解空间搜索范围,提高遗传算法效率;设计了多种交叉操作和变异操作,来增加解的多样性,避免算法陷入早熟;设计了变异概率P,保证了算法的收敛性.实验结果验证了该模型和算法的有效性,从而有效提高集卡运输效率.The truck dispatching is an important way to improve the efficiency of port logistics. In order to meet the re-quirements of rapid loading or unloading containers,loading and unloading of container truck scheduling simultaneously emerged. However,the problem is seldom considered. Here, in case two boats, an improved model about loading and unloading of trucks at the same time was given. And based on it,a new GA was presented. In order to reduce the time during seeking the best solution, the method of N6 neighborhood was proposed to improve the efficiency of GA. To increase the diversity and avoid the premature convergence,a combination of several crossover and mutation operations was introduced. The convergence was assured by the mutation probability P. The experimental results show the correctness and effectiveness of the hybrid genetic algorithm.

关 键 词：改进混合遗传算法 集卡调度 动态优化 N6邻域 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构] O029[自动化与计算机技术—计算机科学与技术]