摘要
针对铁路集装箱堆场混堆区中的零散箱箱位分配问题,在集装箱到达时间和离开时间已知的条件下,建立一个计划期内以倒箱次数最少为目标的多时段动态集装箱堆场箱位分配模型。在计划期内将每时段起重机作业按顺序划分为提箱和卸车两个过程,采用5组0-1变量刻画两种作业、作业前后集装箱的状态以及箱位的状态,由此建立非线性0-1规划模型。考虑到模型所刻画的问题具有NP-hard性质,设计遗传算法求解。算例表明:该模型及算法能够有效地优化堆场内零散箱的箱位分配,提高集装箱堆场的作业效率。
Given that the container arrival time and departure time are known,the multistage dynamic container storage allocation model is established,whose objective is to minimize the rearrangement times of scattered containers in a planning period in the mixed storage area of a container yard.Gantry crane operations are divided into the pick-up process and unloading process in every stage of the planning period according to load sequencing.Five suites of 0-1 variables are employed to describe the two processes of operations and the container states and container position states before and after operations.The nonlinear 0-1 programming model is set.Considering the NP-hard character of the described issues,the genetic algorithm is designed to find the solution.A numerical example shows that the model and algorithm are able to optimize the scattered container storage allocation in mixed storage area effectively and raise the container yard operation efficiency.
出处
《铁道学报》
EI
CAS
CSCD
北大核心
2011年第7期1-7,共7页
Journal of the China Railway Society
基金
国家自然科学基金资助项目(60870008)
教育部新世纪优秀人才支持计划资助(NCET-10-0017)
关键词
集装箱堆场
混堆
多时段
箱位分配
0-1规划
遗传算法
container yard
mixed storage
multistage
container storage allocation
0-1 programming
genetic algorithm
