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...     

单壁钢吊箱在东江四桥主墩承台施工中的应用

结合东江四桥的具体情况，对主墩的承台采用钢吊箱围堰的设计与施工作了全面介绍，对施工方案的选择和施工过程中出现的技术难点作了分析，并从实践出发提出了较为理想的解决措施。加快了进度，节省了投入，可为类似的桥梁下部结构施工提供参考。     

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。     

浅谈拼箱公司经营关键问题及其对策

随着我国对内、对外贸易运输行业的发展,我国的集装箱班轮运输业务也有了很大的发展,日见繁荣,拼箱公司业务也蒸蒸日上。本文首先探究了拼箱公司运输经营的特点所在,接着分析了拼箱公司经营中出现的问题,探索了解决这些问题的几点方法。     

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.     

考虑作业空间干涉的工程项目时间-成本均衡优化研究

工程现场的空间资源是制约工程活动开展的重要影响因素。本文研究考虑空间干涉的工程调度优化问题，定义作业空间干涉的度量方式和作业效率函数，建立工程调度的工期-成本双目标优化模型。针对问题特征设计相对延迟编码方式和解码机制，采用NSGA-II算法求解模型。以某工程案例为研究对象，通过与传统方法对比实验验证了模型和算法的有效性，接着分析了算法的最大延迟时间参数对算法性能的影响。实验结果表明，本文提出的模型和算法能有效提升工程进度和成本目标。     

BROMMA双箱吊具的可靠性改造

厦门集装箱码头集团有限公司海天事业部共有6台BROMMA双箱吊具,平均寿命已经达到10年。由于在作业过程中,吊具直接与箱体接触,冲击很大,加上老化等原因,导致我部BROMMA双箱吊具普遍出现以下问题:(1)中锁无法下;(2)20尺状态下中锁自行下坠;(3)20/40尺限位感应不到;(4)吊具电源经常性损坏,这些问题严重影响了码头生产。对此,我们采取创新思维,通过一系列小技改,大大加强了BROMMA双箱吊具的可靠性。     

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.     

炼钢连铸生产调度问题的两阶段遗传算法

将炼钢连铸生产过程抽象为混合流水车间,建立了0-1型混合整数线性规划调度模型。模型将严格连续浇注作为等式约束,并通过分段惩罚来平衡炉次的驻留时间。在对模型进行Benders分解的基础上,提出了将GA与LP结合的两阶段遗传算法。在算法设计中,提出了一种新的染色体编码来表示炉次设备指派与排序方案,给出了相应的遗传操作方法。算法的第一阶段通过最小化设备析取冲突来寻找高质量的种群,第二阶段通过求解线性规划模型来指导遗传算法的迭代过程。基于生产实际数据的仿真实验表明,该算法能够有效求解炼钢连铸生产调度问题。     

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.     

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.     

A solution framework for the multi-mode resource-constrained cross-dock scheduling problem

In this paper we propose a framework for shift-level container scheduling and resource allocation decisions at a cross-dock facility. The Multi-Mode Resource-Constrained Cross-Dock Scheduling Problem (MRCDSP) approach minimizes material flow and schedules inbound and outbound containers to dock-doors such that the total processing time is minimized subject to the resource constraints at the cross-dock. While container scheduling and resource allocation problems at cross-dock facilities have been studied previously in isolation, our work is the first to consider a complete view of cross-dock operations providing optimal container to dock-door allocation, and a makespan minimizing schedule of containers to the cross-dock. We present a comprehensive framework that includes identification of container clusters to reduce the problem size, a container-to-dock-door assignment algorithm, and a container clusters scheduling model that is solvable for practically sized problems. In a comparative numeric study based on data simulating a cross-dock facility, our approach is shown to outperform current practice, reducing the average time required for processing a set of containers by 37% and reducing the weighted-distance material traveled within the cross-dock by 45%.     

等待时间受限的置换流水车间调度启发式算法

针对等待时间受限的置换流水车间调度问题,分析了其可行解与流水车间调度最优解的关系,给出了计算最大完工时间的有向图,证明了等待时间受限的置换流水车间调度问题的可逆性,并以此为基础提出了一种启发式算法.算法首先根据等待时间受限约束与无等待(no-wait)约束的相似特征,生成初始工件序列集;然后利用问题可逆性给出了复杂度为O(n2m)的插入优化机制,进一步优化初始解.数据实验的结果验证了启发式算法的可行性和有效性.     

Managing appointments with waiting time targets and random walk-ins

The random arrivals of walk-in patients significantly affect the daily operations of healthcare facilities. To improve the performance of outpatient departments, this paper attempts to make an appointment schedule by considering walk-ins and the waiting time target (WTT) for appointment patients. A stochastic programming model is proposed to solve this problem with the objective of minimizing the weighted patient waiting and makespan cost. A non-decreasing waiting cost function is used to capture the WTT fulfillment of appointment patients, whereas walk-ins incur a linear waiting cost. A finite-horizon Markov Decision Process model is formulated to establish the optimal real-time scheduling policy under a given appointment schedule. The appointment schedule is determined by a two-stage stochastic programming approximation and a local search improvement. Structural properties of the optimal appointment scheduling and real-time scheduling policies are established. In particular, it is shown that appointment overbooking is allowed only at the end of the regular session, and the optimal real-time scheduling policy is an easy-to-implement threshold policy with bounded sensitivity. Numerical experiments based on real data are performed to investigate the influence of different parameters and to compare different schedules. The optimal schedule demonstrates superior performance by allowing reasonable waiting times for appointment patients depending on their WTTs. Managerial insights are also provided to hospital managers. Finally, the basic model is extended by incorporating random service times and random arrivals of appointment patients. The latter includes the random number of patients that show up for service or call for appointments, and the random arrival time (unpunctuality). Appointment overbooking strategies are shown to have different structures under some stochastic factors.     

基于风险的考虑成本和允许等待的车辆运输调度问题研究

本文同时考虑了成本约束和允许等待情形,研究了最小化风险的车辆运输调度问题,其中运输风险是随时间不同而变化的,即研究在时间依赖网络中基于风险的有约束的运输路径选择问题,以及在选定路径的顶点上决定的出发和等待时间的综合问题。建立了相应的混合整数规划模型,设计了相应的算法,并分析了算法复杂性,最后通过算例验证了该算法的有效性和可行性。     

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.     

面向并行制造的多生产单元协同调度研究

为提升多生产单元制造系统整体效率，在其系统内开展面向并行制造的协同调度研究，在考虑运输、换线等时间的基础上，构建多生产单元并行协同调度模型，采用并行分段协同遗传算法求解；在此基础上，将所研究协同调度方法应用于某复杂机电产品多生产单元制造车间，并与变批量调度与等批量调度比较。研究表明，所提的并行协同调度方法可以显著提升生产单元效率，提高生产单元设备和人员利用率。