基于泊位偏好与岸桥干扰的泊位和岸桥分配  

Berth and Quay Crane Allocation Considering Berth Preference and Quay Crane Interference

作　　者：乐美龙[1] 刘秀玲[1] 

机构地区：[1]上海海事大学物流研究中心,上海201306

出　　处：《运筹与管理》2014年第1期90-100,共11页Operations Research and Management Science

基　　金：上海市自然科学基金创新行动计划资助项目(10190502500);上海市科委工程中心基金资助项目(09DZ2250400)

摘　　要：泊位和岸桥是集装箱港口资源中最紧缺的资源,合理的泊位分配和岸桥调度可以提高集装箱港口的资源利用率和港口的运作效率和效益。针对泊位偏离和岸桥工作损失两个因素,文章建立了集装箱港口泊位和岸桥的混合整数线性规划模型;运用采集自宁波某典型集装箱港口的数据,用Gurobi优化软件和两阶段启发式算法对模型进行了求解;对计算结果进行了经济性分析。计算结果表明:该港口的岸线资源利用率为46%时,1000m^1600m基本没被利用;18台岸桥要比16台岸桥的目标值更优,求解时间更短,而且18台岸桥的平均利用率为80%,为此,建议该港口再增加两台岸桥。同时发现:随着船舶规模的增加,Gurobi优化求解的时间增长较快,而两阶段启发式算法仍能在很短时间内求得准优解。Berth and quay crane（QC）are the most important scarce resource in the container terminal. Reasona- ble berth allocation and quay crane scheduling can improve utilization of the resources and port operation effec- tiveness and efficiency. The paper firstly presents the integrated MILP model of both berth allocation and QC scheduling based on the deviation from the berth preference position and capacity loss of the QC. Then, using the data from a container terminal in Ningbo and Gurobi optimization solver, we solve the model. Finally the computational result is economically analyzed. The computational results show that the mean utilization rate of berth line of this port is 46%. Among them, the berth line from 1000 to 1600 meter is hardly used, and deplo- ying 18 QCs is better than deploying 16 QCs in the terminal. The mean utilization rate of deploying 18 QCs is 80% , so the paper suggests the port should have two more QCs. Meanwhile we find that as vessels increase, the solving time by Gurobi increases quickly. At the same time, our method, so called two stage heuristic method, can still give the quasi-optimal solution in very short time.

关 键 词：泊位分配 岸桥分配 集装箱港口优化 两阶段启发式算法 集装箱港口经济性分析 

分 类 号：U691.3[交通运输工程—港口、海岸及近海工程]