基于仿真优化的自动化集装箱码头出口箱箱位分配

在集装箱码头堆场中，出口集装箱的箱位分配直接影响集装箱的装船效率以及船舶的在港停留时间。研究主要探讨自动化集装箱码头出口集装箱的箱位分配问题，并将船舶靠泊随机性和出口集装箱集港顺序综合考虑到整数规划模型中。针对模型的特点，设计了基于仿真优化思想的启发式算法求得集装箱贝位分配量，并提出“长途箱压短途箱”的贝内具体落位策略。多组实验结果表明，提出的基于仿真的遗传算法能够有效解决自动化集装箱码头出口箱的箱位分配问题。通过多组算例对比实验发现贝位平均翻箱次数和箱区间作业不平衡度随集装箱数量增加而增加，且“长途箱压短途箱”堆存策略能有效减少未来取箱的翻箱次数。研究结果为智能港口、全自动化集装箱码头的运营提供了思路和方向，有助于实现集装箱码头各子系统一体化效率的提升。     

考虑动态加权A星算法的预翻箱作业优化

为改善堆场作业效率，提出考虑堆场翻箱位规则的集装箱预翻箱作业优化模型并使用动态加权A星算法进行求解，进而确定满足作业规则限制的最优移动序列。基于集装箱装船过程的预翻箱作业，将预翻箱作业过程的贝位布局抽象为A星算法的状态节点，以错误堆叠箱和翻箱迭代深度计算总成本函数，引入动态加权因子控制翻箱迭代方向，提出新颖的搜索分支规则选择有效分支进行搜索。通过上海港码头和相关文献的算例进行实验，结果表明，设计的动态加权启发式函数能够有效改善寻优过程中跳出局部最优解的能力，验证了考虑堆场运作规则-翻箱位规则的算法有效性和稳定性。研究成果能够普遍适用于作业工艺和贝位布局不同的集装箱码头预翻箱作业，能够为堆场运作优化提供决策参考。     

考虑出口箱进出场及预翻箱的箱位分配与场桥调度协同优化

为降低送箱集卡到场的不确定性对出口箱堆存和装船效率的影响,以最小化堆场进出场作业系统总作业时间为上层模型的目标,以最小化同一批入场出口箱的堆存时间下层模型的目标,构建了双层混合整数规划模型为进出场的出口箱分配箱位并优化场桥调度。设计改进的遗传模拟退火算法求解上层模型可得出口箱箱位分配方案,求解下层模型可得预翻箱和场桥调度方案,通过不断平衡上下层最优解使堆场堆存和装船作业效率最优。通过数值实验验证了算法和调度策略有效性,研究结果可丰富集装箱码头运营系统优化理论,为提高出口箱堆场作业效率提供决策参考。     

考虑码头内外堆场竞争的集装箱堆存定价模型

针对由于集装箱吞吐量增加造成翻箱成本增加与码头堆场拥堵,考虑内外堆场竞争,构建集装箱堆存定价模型,研究内外堆场竞争下的堆存定价决策和货主移箱决策,分析码头堆场操作成本、场外堆场运输成本、货主需求参数和码头堆场收益的内在关系。算例结果表明:一旦过了免费期立即移箱到场外堆场,货主成本最小。随着场外堆场运输成本的增加,码头堆场的堆存定价和箱量增加,提高码头堆场收益。随着码头堆场操作成本降低,码头堆场堆存价格随之下降,但码头堆存箱量增加,提高码头堆场收益。此外降低堆场定价对货主需求的影响参数以及提高运输成本对货主需求的影响系数,有利于提高码头堆场收益。     

集装箱码头堆场翻箱与外集卡提箱顺序同步优化方法

针对集装箱码头提箱作业过程中,由于外集卡的提箱顺序与目标箱在堆场的堆存位置不匹配导致大量翻箱这一难题,以码头的作业成本和外集卡的延误成本之和最小为目标,建立堆场翻箱与外集卡提箱顺序同步优化模型,优化外集卡的提箱顺序、龙门吊的任务分配以及翻箱方案。设计基于动态规划的启发式算法求解模型,并利用算例对模型与算法的有效性进行了验证。结果表明:与目前码头普遍采用的提箱方式相比,通过调整外集卡提箱顺序并同时优化翻箱方案以及龙门吊的任务分配可以降低堆场翻箱率,减少龙门吊的移动成本,从而节省提箱作业的总成本。     

基于贪婪禁忌搜索算法的垂岸式堆场出口箱装船翻箱研究

基于垂岸式自动化集装箱码头不同装船周期出口集装箱堆场多贝位混合堆存、场桥大车在贝位间频繁移动取箱装船特点,考虑装船发箱时场桥移动等操作时间及翻箱取箱次数对出口箱装船效率和连续性影响,建立多贝位出口箱装船堆场翻箱模型,提出两阶段贪婪禁忌搜索算法,将翻箱规则嵌入算法中,有效限制算法时间和解空间增长速度。通过算例,将提出的翻箱规则与现有常见翻箱规则进行对比,验证模型及算法的有效性与实用性。结果表明,提出的模型和算法可以在合理的求解时间内输出较优的翻箱方案,减少装船时场桥发箱作业时间,提高装船作业效率。     

考虑翻箱的场桥调度和提箱集卡数量的集成优化

在集装箱码头的进口箱堆场中,码头预约机制、待提箱的实时位置和场桥作业调度方案是制约堆场作业效率和堵塞情况的关键。为缓解进口箱堆场的拥塞情况并提高作业效率,在固定的预约时段内,考虑实时压箱量最少的翻箱规则,兼顾场桥间不可跨越和保持安全间距等现实约束,以场桥最长完工时间最小为目标,构建数学优化模型,设计了嵌入修复算子的改进遗传算法用于求解;通过算例实验验证了算法的有效性和方案的优越性,可为堆场实际作业提供决策参考。     

预倒出口箱区的多场桥调度优化

在集装箱出口箱区堆场的实际作业中,常将待提箱提前翻倒至一空闲箱区,使其装船前以船舶配载图的倒序堆垛,以提高装船效率。为提高初始出口箱区的预翻作业效率,针对该箱区的多场桥调度优化问题进行研究。以实施预翻作业的某一出口箱区为研究对象,在船舶配载图已知的前提下,考虑作业场桥间保持安全距离且不可跨越的条件,兼顾满足经验翻箱规则等现实约束,侧重作业过程中实时翻箱,构建了以场桥作业总行走时间最小为优化目标的线性规划模型,并设计了分支定价算法。在算例实验中,通过与非实时预翻箱方案、FCFS方案以及下界进行对比,验证了模型及算法的有效性,可为集装箱码头出口箱堆场的场桥调度提供参考。     

关于合理确定集装箱码头装船顺序的算法

如何在给出箱区图和配载图的情况下,根据不同的装船方式,运用计算机程序确定合理的发箱和装箱顺序?本文主要依据实际数据,针对两种在码头实际装船作业中应用性较强的装船方式进行了研究,分别对其做了建立数学矩阵模型,制定合理算法,编写M ATLAB程序等工作,并论证了它们在实际操作中的可行性.本文的研究结果会在集装箱码头的实际装船作业中具有很强的应用性.     

集装箱倒箱问题的模型与启发式算法研究

本文研究了集装箱堆场中集装箱搬运的优化问题.利用以7个倒箱落位步骤为核心的启发式算法,建立轨道式龙门机取箱作业的数学模型,获得了最小化倒箱量的方法.推广了大规模倒箱问题的结果,具有较好的实际意义.     

Determining crane areas in intermodal transshipment yards: The yard partition problem

At rail–road transshipment yards, gantry cranes move containers from freight trains to trucks and vice versa. They constitute important entities in today’s intermodal transportation systems. Real-world yards are often partitioned into several disjunct crane areas, so that crane interferences during container transshipment are avoided. In practice, the lengths of such crane areas are typically determined by simple rules of thumb, i.e., each crane receives an equally sized area, which might result in an unleveled division of labor among cranes and, thus, prolong train processing times. This paper provides an exact solution procedure which determines disjunct yard areas of varying size for multiple gantry cranes in polynomial runtime, so that the workload for a given pulse of trains is equally distributed among cranes. Furthermore, we investigate the potential acceleration of train processing as compared to equally sized areas in a yard simulation.     

A note on deriving decision rules to locate export containers in container yards

A counterexample is given to illustrate that a key model transformation in the paper entitled “Deriving decision rules to locate export containers in container yards” [Kim, K.H., Park, Y.M., Ryu, K.-R., 2000. Deriving decision rules to locate export containers in container yards. European Journal of Operational Research 124 (1), 89–101] is not correct. Then, the errors in the original derivation of the model transformation are analyzed, and the correct form is presented.     

Storage yard operations in container terminals: Literature overview,trends, and research directions

Inbound and outbound containers are temporarily stored in the storage yard at container terminals. A combination of container demand increase and storage yard capacity scarcity create complex operational challenges for storage yard managers. This paper presents an in-depth overview of storage yard operations, including the material handling equipment used, and highlights current industry trends and developments. A classification scheme for storage yard operations is proposed and used to classify scientific journal papers published between 2004 and 2012. The paper also discusses and challenges the current operational paradigms on storage yard operations. Lastly, the paper identifies new avenues for academic research based on current trends and developments in the container terminal industry.     

Storage space allocation models for inbound containers in an automatic container terminal

This paper studies the problem of improving the operations efficiency for retrieving inbound containers in a modern automatic container terminal. In the terminal, when an external truck arrives to collect a container stored in a specific container block, it waits at one end of the block where an automatic stack crane will retrieve the container and deliver it to the truck. With the aim of reducing the expected external truck waiting time which is determined by how the containers are stored in a block, we propose two correlated approaches for the operations efficiency improvement, (1) by designing an optimized block space allocation to store the inbound containers after they are discharged from vessels, and (2) by conducting overnight re-marshaling processes to re-organize the block space allocation after some containers are retrieved. For the block space allocation problem, we consider three optimization models under different strategies of storing containers, namely, a non-segregation model, a single-period segregation model, and a multiple-period segregation model. Optimal solution methods are proposed for all three models. For the re-marshaling problem with a given time limit, we find that the problem is NP-hard and develop a heuristic algorithm to solve the problem. We then use simulation to validate our models and solution approaches. Simulation results reveal important managerial insights such as the advantage of the multiple-period segregation over the myopic single-period segregation, the possibility of overflow of the segregation model, and the benefit of re-marshaling.     

Yard crane scheduling in port container terminals

Yard cranes are the most popular container handling equipment for loading containers onto or unloading containers from trucks in container yards of land scarce port container terminals. However, such equipment is bulky, and very often generates bottlenecks in the container flow in a terminal because of their slow operations. Hence, it is essential to develop good yard crane work schedules to ensure a high terminal throughput. This paper studies the problem of scheduling a yard crane to perform a given set of loading/unloading jobs with different ready times. The objective is to minimize the sum of job waiting times. A branch and bound algorithm is proposed to solve the scheduling problem optimally. Efficient and effective algorithms are proposed to find lower bounds and upper bounds. The performance of the proposed branch and bound algorithm is evaluated by a set of test problems generated based on real life data. The results show that the algorithm can find the optimal sequence for most problems of realistic sizes.     

Conservative allocation models for outbound containers in container terminals

This paper examines location assignment for outbound containers in container terminals. It is an extension to the previous modeling work of Kim et al. (2000) and Zhang et al. (2010). The previous model was an “optimistic” handling way and gave a moderate punishment for placing a lighter container onto the top of a stack already loaded with heavier containers. Considering that the original model neglected the stack height and the state-changing magnitude information when interpreting the punishment parameter and hid too much information about the specific configurations for a given stack representation, we propose two new “conservative” allocation models in this paper. One considers the stack height and the state-changing magnitude information by reinterpreting the punishment parameter and the other further considers the specific configurations for a given stack representation. Solution qualities for the “optimistic” and the two “conservative” allocation models are compared on two performance indicators. The numerical experiments indicate that both the first and second “conservative” allocation models outperform the original model in terms of the two performance indicators. In addition, to overcome computational difficulties encountered by the dynamic programming algorithm for large-scale problems, an approximate dynamic programming algorithm is presented as well.