基于Multi-Agent的集装箱码头物流作业重构

在介绍集装箱码头物流作业流程的基础上,通过引入计算Agent和作业角色Agent构建了基于Multi_Agent的集装箱码头物流作业重构系统结构,并说明了重构中作业角色Agent的工作过程,用强化学习算法设计了作业角色Agent.接着阐述了在基于Multi_Agent的集装箱码头物流作业重构中计算Agent重构模型,以及用对策论和社会规则相结合实现相邻作业角色Agent的协调.最后,以某集装箱码头泊位作业和岸桥作业两相邻作业重构进行了数据分析,证明了重构的有效性.     

集装箱码头外部集卡预约优化模型与算法

针对集装箱码头闸口拥堵问题,建立集卡预约优化模型,目的是减少集卡排队等待时间和拥堵期间的碳排放。该模型在给定的集卡到达调整量水平的限制下,确定每个时段最优的预约份额,同时利用非平稳排队模型描述集卡到达随时间到达的特点。为求解模型,设计基于遗传算法与逐点固定流体近似算法(PSFFA)的求解方法,该算法利用遗传算法搜索最优解,基于PSFFA算法计算集卡排队时间。最后,利用算例对模型和算法的有效性进行了验证。结果表明,集卡预约优化模型可以有效地减少集卡排队时间,PSFFA方法可以较好地求解到达过程不平稳的排队问题。     

集装箱枢纽港主辅码头间靠泊决策的协同优化

近年来集装箱枢纽港码头拥挤问题日益突出,船舶等泊时间的延长导致船公司经营成本增加,尤其对于经营支线运输的船公司而言更是如此.鉴于此,船公司在拥挤的集装箱枢纽港码头附近设置趸船或驳船作为辅助码头来停泊箱量较小的船舶,通过建立缓冲区以减少等泊时间及降低停泊费用.本文从集装箱支线运输公司经营人的角度,首次提出了集装箱枢纽港主辅码头间的靠泊决策的协同问题,基于泊位调度理论建立了靠泊决策的协同优化模型,并用改进的遗传算法求解.仿真实验定量分析并证实了设置浮动码头对集装箱支线运输公司减少等泊时间及降低成本的有效性.     

集装箱码头泊位计划干扰恢复多目标模型

研究集装箱码头中干扰事件发生后泊位计划的调整问题,目的是降低干扰事件对集装箱码头作业系统的干扰.基于干扰管理方法,建立泊位计划干扰恢复多目标、多阶段模型,该模型考虑码头不同客户的特点以及多方利益的平衡,从码头作业成本、船舶延误以及计划偏离度三个方面度量系统扰动.为求解模型,提出了基于字典续的求解方法,并利用算例对模型与算法的有效性进行了验证.结果表明:该模型与算法可以有效解决泊位计划调整问题,模型能够考虑各方的利益以及码头各类客户的特点,因此得到的泊位调整方案更科学,同时,模型各目标的重要顺序可根据情况进行调整,实用性与可操作性更高.     

集装箱码头作业系统堆场作业管理策略分析

提升集装箱的装卸效率是当前集装箱码头发展中所面临的主要问题。文中简要阐述了加强集装箱码头堆场管理所具有的重要意义,并对当前集装箱码头作业系统堆场作业管理策略和提升集装箱码头作业系统堆场作业管理效率的有效策略进行了详细分析。     

基于混合流水作业组织的集装箱码头装卸作业集成调度优化

集装箱码头集疏运资源调度的对象是由岸桥、集卡、场桥所构成的多阶段一体化的集装箱装、卸、运操作系统,将该系统的调度优化基于多阶段混合流水线调度问题建立混合整数规划模型,同时考虑集装箱码头现实作业中预定义顺序、避免岸桥交叉作业、以及取决于作业顺序的切换时间等现实约束,针对问题自身的特点设计了两阶段启发式算法,得出各阶段设备的指派结果及作业顺序。通过与基于现行调度规则的调度方案以及与目标函数理论下界值的对比实验,显示了所提出的集成调度模型及求解算法能够有效降低船舶在港时间并实现集卡资源的共享,为集装箱码头集疏运资源的集成调度提供了新的思路。     

集装箱码头堆场取箱时间窗优化研究

码头堆场是供装卸船舶存放集装箱的场所,同时也是向货主交接集装箱的地方.由于取箱车辆到达时间的不确定性,码头运营方需要在堆场进行大量的翻箱作业,消耗大量的劳动成本.首先对码头取箱时间窗优化机制进行了说明,构建了码头方补助金函数与车辆方的成本函数,获得了车辆方取箱的到达率函数,进而得到了码头方的翻箱次数公式.然后,描述了集...     

基于运载能力的集装箱码头集卡调度优化方法研究

集卡是集装箱码头的重要资源,集卡的运载能力允许其单次可运输一个20 ft集装箱、两个20 ft集装箱或一个40 ft集装箱。而目前有关集卡调度的研究往往以单位集卡重载一个集装箱为作业单元,即“一车一箱”的运输模式,忽视了对集卡实际运载能力的讨论。本文考虑集卡对于不同箱型集装箱的实际运载能力,对进口箱卸箱过程的集卡调度问题进行研究。首先构建了以卸箱作业完成时间最小为目标的混合整数规划模型,随后证明了问题是NP完全问题,并设计了多起点自适应邻域搜索算法进行求解。计算结果表明,相比于规划求解器,算法可以在更短时间内求得问题的近优解;相比于“一车一箱”的运输模式,本文的集卡调度方案可使卸箱作业完成时间平均缩短23.5%。研究基于集卡的实际运载能力优化集卡调度方案,能够有效缩短船舶在港作业时间,可为集装箱码头实际作业过程中的集卡调度提供依据。     

虚拟顾客服务系统排队模型

通过对虚拟企业售后服务部门的顾客排队网络的分析 ,确定了一种顾客具有优先权的多级顾客服务排队模型 .以顾客满意度为条件计算出了稳定平衡状态下排队系统的主要指标 ,并从收益、成本和效率等方面建立了排队系统的优化问题 ,从而可得到服务部门最优基准服务能力 .基准服务能力的确定 ,对服务能力的有效安排和组织具有重要的指导意义     

竞争环境下的轴-辐式集装箱海运网络设计问题

针对航运企业的重组与全球扩张引起的竞争问题,提出了竞争环境下的轴-辐式集装箱海运网络设计模型。模型采用基于路径的变量作为决策变量,利用离散函数来表示航运企业与航运联盟的竞争可吸引的流量(或客户),目的在于通过设计混合轴-辐式集装箱海运网络,实现以更低的服务成本和更短的服务时间最大化可吸引的流量,建立了枢纽港口数量约束、航线连接约束、航线中转约束、流量竞争约束等,运用多点交叉遗传算法进行求解,最后结合亚欧航线的集装箱海运市场进行实例分析,对考虑客户需求多样性与航运联盟对策下的轴-辐式集装箱海运网络进行设计,并验证了算法的计算效果。     

A rostering approach to minimize health risks for workers: An application to a container terminal in the Italian port of Genoa

The evolving safety regulation is pushing seaports to comply with safety measures for workers performing heavy loads handling and repetitive movements. This paper proposes a risk-aware rostering approach in maritime container terminals, i.e., it addresses the rostering problem of minimizing and balancing workers’ risk in such terminals. To this end, a mixed integer mathematical programming model incorporating workforce risks is proposed, considering constraints such as the satisfaction of the workforce demand to perform the terminal operations, the worker-task compatibility and restrictions on the sequence of tasks assigned to the same worker. The model has been successfully applied to plan workforce over a six months horizon in a real container terminal located in Northern Italy, the Southern European Container Hub (SECH) in Genoa. As the workforce demand in SECH terminal is available at most two weeks in advance, a rolling horizon planning approach is devised. Experimental tests on real data provided by SECH terminal over a six months planning horizon highlight the effectiveness of the approach - the maximum monthly risk for workers is reduced by 33.9% compared to the current planning – and suitability to other container terminal contexts. Moreover, the model is applicable to a broad range of port situations, and robust enough to need little adaptation.     

Online integrated allocation of berths and quay cranes in container terminals with 1-lookahead

This paper studies an online over-list model of the integrated allocation of berths and quay cranes (QCs) in container terminals with 1-lookahead ability. The objective is to minimize the maximum completion time of container vessels, i.e., the makespan. We focus on two different types of vessels, three berths and a small number of QCs in the hybrid berth layout, with 1-lookahead ability. We propose a \({{(1 + \sqrt{2} )/2}}\)-competitive algorithm for the case with four cranes, a 5/4-competitive algorithm for the case with five cranes and a 4/3-competitive algorithm for the case with six cranes, respectively. All of the algorithms are proved to be optimal.     

Scheduling material handling vehicles in a container terminal

Increasing global trade has created the need for efficient container ports. The goal of the port is to move containers as quickly as possible and at the least possible cost. Goods that are delayed at the port are inevitably tardy when delivered to the customer, and thus sanctioned by late charges. Two key activities in the port are (i) unloading of containers from truck and then storage in the export area, and (ii) removal of containers from import storage and then loading onto the trucks. Since containers are large and heavy, specialized material handling vehicles are required for transporting them within the terminal. The focus of this paper is on port terminals where straddle carriers are primarily used to move containers. Container terminals typically have well developed computer and communication networks. Through these networks a terminal scheduler will control and schedule the movement of the straddle carrier fleet in real time. The objective of the terminal scheduler is to minimize the empty travel of straddle carriers, while at the same time minimizing any delays in servicing customers. This paper presents a straddle scheduling procedure that can be used by a terminal scheduler to control the movement of straddle carriers. At its core, the procedure is driven by an assignment algorithm that dynamically matches straddle carriers and trucks, as each becomes available. The procedures were developed and tested in collaboration with the largest container terminal operator in the Port of New York and New Jersey. Using a simulation model of the real system, the superiority of the proposed procedure over two alternative scheduling strategies is illustrated.     

Target-guided algorithms for the container pre-marshalling problem

The container pre-marshalling problem (CPMP) aims to rearrange containers in a bay with the least movement effort; thus, in the final layout, containers are piled according to a predetermined order. Previous researchers, without exception, assumed that all the stacks in a bay are functionally identical. Such a classical problem setting is reexamined in this paper. Moreover, a new problem, the CPMP with a dummy stack (CPMPDS) is proposed. At terminals with transfer lanes, a bay includes a row of ordinary stacks and a dummy stack. The dummy stack is actually the bay space that is reserved for trucks. Therefore, containers can be shipped out from the bay. During the pre-marshalling process, the dummy stack temporarily stores containers as an ordinary stack. However, the dummy stack must be emptied at the end of pre-marshalling. In this paper, target-guided algorithms are proposed to handle both the classical CPMP and new CPMPDS. All the proposed algorithms guarantee termination. Experimental results in terms of the CPMP show that the proposed algorithms surpass the state-of-the-art algorithm.     

Erlang风险模型有限时间的破产概率

Erlang风险模型广泛应用于排队论、控制论以及金融风险过程.本文在索赔来到(claim-arrival)为Erlang过程,索赔额服从帕雷托分布以及具有常数利息力度的假设下,得到了有限时间内破产概率的渐近表达公式.该结果实质性地推广了Kluppelberg and Stadtmuller[1]和Tang[2]的结果:前者考虑了无穷时间的破产概率,而后者考虑的过程局限为泊松的.由破产模型与排队模型之间的联系可知,本文的结果在管理科学中有许多应用.     

基于“云排队”的经济效益分析

随着各种云智能排队预约系统的推出，顾客“排队难”的问题得到了极大的缓解。其简便的操作方式，受到了大量商家与顾客的好评。本文基于当下热门服务行业的运营模式，建立排队博弈模型，从理论上分析了“云排队”平台对顾客以及服务商的影响。本文主要得到了以下几个结果：(1) 给出了两类顾客的纳什均衡策略(包括进队策略与最优到达间隔)；(2) 发现当前的预约机制能够提高“线上”顾客的效用，并刺激更多的线上顾客购买该产品，但同时也降低了“线下”顾客的进队意愿；(3) 发现在云排队机制下服务商的收益将大大提高，同时该机制将刺激服务商收取更高的服务费用。     

集装箱班轮二维收益管理在线动态定价策略

为了在现实约束条件下最大化班轮公司收益,研究了集装箱海运二维收益管理多航段多箱型在线动态定价模型,提出了其最优在线动态定价策略,并且证明了模型价值函数的单调性及其上界.基于降维的思想提出了更为实际的启发式算法.在算例中分析了单航段单箱型、单航段多箱型和多航段多箱型3种情况下的最优动态定价策略,分析结果表明:在单航段单箱型的情况下,最优价格具有单调性;在单航段多箱型和多航段多箱型的情况下,最优价格不一定具有单调性.