In order to improve the operational efficiency and reduce the operational cost of container terminal yard, this paper studies the integrated optimization of storage space allocation and multiple yard cranes scheduling in a container terminal yard. The regional workload balance planning method is adopted to make yard working plan, and an integrated optimization model of storage space allocation and multiple yard cranes scheduling is established. It reduces the idle cost and moving cost of yard cranes considering the safety distance and workload balance between yard cranes. The simulated annealing operation is introduced to improve the global search ability of genetic algorithm. A simulated annealing genetic algorithm is designed to solve the model. The effectiveness of the adopted algorithm is verified by numerical experiments and the results show that the regional workload balance planning method can better solve the integrated optimization of storage space allocation and multiple yard cranes scheduling.
FAN Houming,MA Mengzhi,Yao Xi,GUO Zhenfeng
. Integrated Optimization of Storage Space Allocation and
Multiple Yard Cranes Scheduling in a Container Terminal Yard[J]. Journal of Shanghai Jiaotong University, 2017
, 51(11)
: 1367
-1373
.
DOI: 10.16183/j.cnki.jsjtu.2017.11.013
［1］LEE Y, HSU N Y. An optimization model for the container pre-marshalling problem［J］. Computers & Operations Research, 2007, 34(11): 3295-3313.
［2］SHARIF O, HUYNH N. Storage space allocation at marine container terminals using ant-based control［J］. Expert Systems with Applications, 2013, 40(6): 2323-2330.
［3］CHEN L, LU Z. The storage location assignment problem for outbound containers in a maritime terminal［J］. International Journal of Production Econo-mics, 2012, 135(1): 73-80.
［4］周鹏飞, 方波. 动态环境下集装箱码头堆场出口箱箱位分配建模与算法研究［J］. 控制与决策, 2011, 26(10): 1571-1576.
ZHOU Pengfei, FANG Bo. Modeling and algorithm research on export container slots allocation under dynamic environments［J］. Control and Decision, 2011, 26(10): 1571-1576.
［5］LI W K, WU Y, PETERING M E H, et al. Discrete time model and algorithms for container yard crane sche-duling［J］. European Journal of Operational Research, 2009, 198(1): 165-172.
［6］HE J L, HUANG Y F, YAN W. Yard crane sche-duling in a container terminal for the trade-off between efficiency and energy consumption［J］. Advanced Engineering Informatics, 2015, 29(1): 59-75.
［7］郑红星, 于凯. 基于混合遗传算法的混堆箱区内场桥调度研究［J］. 交通运输系统工程与信息, 2013, 13(5): 150-158.
ZHENG Hongxing, YU Kai. Yard crane scheduling in the mixture storage block base on hybrid genetic algorithm［J］. Journal of Transportation System Engineering and Information Technology, 2013, 13(5): 150-158.
［8］赵磊, 胡志华, 李淑琴. 基于作业均衡的集装箱堆场箱区场桥作业调度［J］. 武汉理工大学学报, 2013, 35(1): 69-74.
ZHAO Lei, HU Zhihua, LI Shuqin. Container yard crane scheduling for operations balance between yard cranes［J］. Journal of Wuhan University of Technology, 2013, 35(1): 69-74.
［9］JIN J G, DERHORNG L, CAO J X. Storage yard management in maritime container terminals［J］. Transportation Science, 2016, 50(4): 1300-1313.
［10］LIANG C, GU T, LU B, et al. Genetic mechanism-based coupling algorithm for solving coordinated scheduling problems of yard systems in container terminals［J］. Computers & Industrial Engineering, 2015, 89(C): 34-42.
［11］张盛意, 蔡之华, 占志刚. 基于改进模拟退火的遗传算法求解0-1背包问题［J］. 微电子学与计算机, 2011, 28(2): 61-64.
ZHANG Shengyi, CAI Zhihua, ZHAN Zhigang. Solving 0-1 knapsack problem based on genetic algorithm with improved simulated annealing［J］. Micro-electronics & Computer, 2011, 28(2): 61-64.
