[1]李尤丰,李勤丰,刘玉霞,等.一种新的集卡动态调度模型及算法[J].南京师大学报(自然科学版),2014,37(01):104.
　Li Youfeng,Li Qinfeng,Liu Yuxia,et al.Dynamic Dispatch Model of Container Trucks Based on Hybrid Genetic Algorithm[J].Journal of Nanjing Normal University(Natural Science Edition),2014,37(01):104.
点击复制

一种新的集卡动态调度模型及算法()
分享到：

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

卷:
第37卷
期数:
2014年01期
页码:
104
栏目:
计算机科学
出版日期:
2014-03-30

文章信息/Info

Title:
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
(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)
Author(s):
Li Youfeng1; Li Qinfeng2; 3; Liu Yuxia4; Zhou Xiaofeng3
(1.College of Information Technology,Jinling Institute of Technology,Nanjing 211169,China) (2.Department of Basic Course,Jinling Institute of Technology,Nanjing 211169,China) (3.College of Information and Computer Engineering,Hohai University,Nanjing 211100,China) (4.Department of Basic Course,The University of International Relations of Chinese PLA,Nanjing 210039,China)
关键词:
改进混合遗传算法; 集卡调度; 动态优化; N6邻域
Keywords:
hybrid genetic algorithm; truck scheduling; dynamic optimization; N6 neighborhood
分类号:
TP301.6; O29
文献标志码:
A
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.
Abstract:
The truck dispatching is an important way to improve the efficiency of port logistics.In order to meet the requirements 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.

参考文献/References:

[1] 丁荣涛.基于协作能力约束的港口集卡调度优化策略[J].清华大学学报:自然科学版,2012,52(8):1 158-1 164.
[2]梁剑,王强,安俊英.铁路集装箱中心站内部集卡调度和箱位配置[J].计算机工程,2012,38(8):213-220.
[3]尚晶.面向双40英尺岸桥的码头集卡调度模型与算法[J].华中科技大学学报:自然科学版,2010,38(11):84-87.
[4]曾庆成,杨忠振.集装箱码头集卡调度模型与Q学习算法[J].哈尔滨工程大学学报,2008,29(1):1-4.
[5]曾庆成.集装箱码头装卸作业集成调度模型与方法[D].大连:大连海事大学计算机科学与技术学院,2008.
[6]Pyung H K,Woon S L,Dong W J.Fleet sizing and vehicle routing for container transportation in a static environment[J].OR Spectrum,2004,26(2):193-209.
[7]Ren Q D E J,Wang Y P.A new hybrid genetic algorithm for job shop scheduling problem[J].Computers and Operations Research,2012,39(10):2 291-2 299.
[8]何大勇,查建中,姜义东.遗传算法求解复杂集装箱装载问题方法研究[J].软件学报,2001,12(9):1 380-1 385.
[9]Glover F,Laguna M.Tabu Search[M].Dordrecht:Kluwer Academic Publishers,1997.
[10]Zhang C Y,Li P G,Guan Z L,et al.A tabu search algorithm with a new neighborhood structure for the job shop scheduling problem[J].Computers and Operations Research,2007,34(11):3 229-3 242.
[11]Van Laarhoven P J M,Aarts E H L,Lenstra J K.Job shop scheduling by simulated annealing[J].Operations Research,1992,40(1):113-125.
[12]Nowicki E,Smutnicki C.A fast taboo search algorithm for the job shop scheduling problem[J].Management Science,1996,42(6):797-813.
[13]Nasiri M M,Kianfar F.A GES/TS algorithm for the job shop scheduling[J].Computers and Industrial Engineering,2012,62(4):946-952.

备注/Memo

备注/Memo:
收稿日期:2013-10-20.
基金项目:江苏省现代教育技术研究课题(2011-R-19470).
通讯联系人:李尤丰,讲师,硕士,研究方向:图像分析和大型软件系统架构、管理.E-mail:flllyf@126.com
更新日期/Last Update: 2014-03-30