区块链平台下航运供应链的两阶段定价研究

考虑到区块链的去中心化技术以及航运供应链中成员的定价决策问题，构建了一条港口-承运商的二级航运供应链。港口建立私有区块链平台与承运商共享市场需求信息，结合信息共享程度系数和成本分担比例系数，构建了在传统模式和基于区块链技术模式下分别进行各自的定价决策模型，并使用Stackelberg博弈对比两种模式下各自定价的最优策略，探讨了在私有区块链平台上不同的信息共享程度对于定价和收益的影响。研究结果发现：港口建立私有区块链平台后，无论信息共享程度如何，总是可以提高承运商的货运批发价和港口的港口批发价；当信息完全共享时，港口的收益最大，但此时承运商需要承担全部的平台构建费用，反而自身的收益会减少从而放弃加入私有区块链平台，为了良性发展承运商可以适当承担一定比例的平台成本，在一定条件下可以达成最优策略。     

基于知识网链的供应链决策系统

从构建基于知识网链的流程供应链决策支持链出发,分析供应链中知识流程的构成要素。针对供应链知识共享的要求,给出基于知识获取、知识共享及知识交流BBS的供应链知识网链框架和建立在信息支持和功能支持基础之上的供应链功能结构。为促进供应链知识网链中知识不断更新,实现知识滚动优化的整体知识网链结构并构建知识网链支持下的供应链决策过程,使供应链的运行建立在知识基础之上,使供应链变成。个具有知识采集、知识存储、知识共享、知识应用的知识网链,使知识网链成为供应链的决策支撑链。     

延迟时间Petri网的验证分析

延迟时间Petri网（Delay Time Petri Nets，DTPN）是一类重要的时间扩展Petri网系统，解决了其他时间扩展Petri网（如时间Petri网）在保存时间约束时所面临的困难。可调度验证的目的是验证工作流模型时间约束的合理性，对流程实例的时间可达性进行仿真。提出一种基于DTPN的时间约束工作流验证分析方法。给出了DTPN的相关定义，并结合工作流控制结构描述了变迁可触发的时间条件；提出了DTPN触发点的概念以及基于此的验证分析算法；简要分析了DTPN的特性。DTPN的研究丰富完善了现有时间Petri网体系，具有积极的意义。     

基于联盟区块链的农产品质量安全高效追溯体系

针对农产品追溯系统中的安全和效率问题，依据区块链的去中心化安全特性，提出一种基于联盟区块链的高效解决办法。首先，通过星际文件系统（IPFS）对农产品数据进行hash转变，从而减小区块中单条事务数据量，并利用IPFS数据的不可逆原理，达到数据的初步保障；其次，建立联盟区块链模型进行数据验证，区块链数据验证的共识算法采用实用拜占庭容错（PBFT）算法来减少全网共识时间；最后，根据仿真实验中参与节点数、区块大小和网络带宽，来拟合验证交易的时间曲线，进而计算出不同带宽下的区块链交易效率，并结合数以万计的传感器参与下的农产品追溯系统的实际情况，对比区块链双链结构，给出分析结果。实验结果表明，在低于1000个验证节点的条件下，区块链最大共识时长为32 min，联盟链系统可支持35~40万条传感器数据，可适用于大范围、多数据的农产品追溯。     

基于层次Petri网的复杂装备保障流程分析方法

针对复杂装备保障流程约束条件多、动态性强、耦合严重、层次结构复杂的特点,提出了一种基于层次Petri网的流程分析方法;首先,分析了保障流程的层次化结构,采用着色时间约束Petri网,建立了包含保障人员、保障设备、保障空间等保障资源库所的层次化Petri网流程模型;然后,采用流程基本模型起始时间——流程子网起始时间——流程总时间的层次方法,设计了流程时间参数统计算法;最后,以某复杂装备系统保障流程为例,进行了实例分析,并通过与ExSpect软件MonteCarlo仿真对比验证了算法的有效性.     

微流程的建模与分析

业务流程管理技术是组织实施信息系统的重要使能技术.为确保微流程能正常运行,提出了一种建模与分析微流程的方法.首先,该方法以Petri网为形式化基础,对微流程以及微流程间的同步组合和异步组合进行建模.其次,基于Petri网的分析技术,该方法对组合微流程进行了合理性分析.实验结果表明,该方法能建模微流程,并检测出组合微流程...     

基于区块链的5G物联网数据共享方案

海量的物联网数据拥有巨大价值,而现有基于云的数据共享机制,面临单点故障、内部泄露等问题,无法确保用户数据的安全共享。为实现高效可信的数据共享,利用区块链技术,提出了基于区块链的5G物联网数据共享方案。该方案首先设计了数据共享框架和数据共享流程;然后基于闪电网络方案,提出了面向物联网数据共享的链下交易机制。实验分析表明,基于区块链的5G物联网数据共享方案具有较强的抗攻击能力;基于闪电网络的交易机制,能够大幅提高交易吞吐量、降低交易时延。     

一个基于TWF-net的扩展时间工作流模型及其应用

时间约束是分布式企业工作流程建模中的一个重要因素．基于时间Petri网工作流模型(TWF-net)，通过分析TWF-net模型不足之处，建立了一种新的时间Petri网工作流模型——扩展时间Petri网工作流模型(XTWF-net)．通过构建规则，可将多个TWF-net合并为一个XTWF-net，以描述并行流程中的时间约束；通过引入与时区相关的时间映射函数，XTWF-net可以描述分布于不同时区的流程．最后给出一个利用XTWF-net描述分布式企业中业务流程的实例．     

基于区块链技术的物联网信息共享安全机制

针对物联网（IoT）信息共享中存在的源数据易被篡改、缺乏信用保障机制以及信息孤岛问题，提出一种基于区块链技术的轻量级物联网信息共享安全框架。该框架采用数据区块链和交易区块链相结合的双链模式:在数据区块链中实现数据的分布式存储和防篡改，并通过改进的实用拜占庭容错（PBFT）机制共识算法，提升数据登记效率；在交易区块链中实现资源和数据交易，并通过基于部分盲签名算法的改进算法，提升交易效率、实现隐私保护。仿真实验部分分别针对抗攻击能力、双链的处理能力和时延进行了验证分析，结果表明该框架具有安全性、有效性和可行性，可应对现实物联网中的大部分场景。     

基于SM2国密算法优化的区块链设计

针对当前区块链系统使用的ECDSA公钥签名算法存在后门安全隐患的问题,提出采用SM2国密算法替换ECDSA公钥签名算法的区块链设计.对SM2国密算法进行详细研究后发现,为突破该算法中较为复杂的椭圆曲线计算以及较高时间复杂度的性能瓶颈,在不影响算法本身安全性的前提下,对算法的核心加密流程进行优化,设计基于已知随机数值序列优化的SM2算法,完成基于优化SM2算法的区块链设计.对优化后的国密算法和区块链系统进行仿真实验与分析,验证了优化后国密算法的有效性和区块链系统的高效性.     

海铁联运港口混合作业模式下轨道吊与集卡协同调度

在集装箱海铁联运港口中,铁路作业区作为连接铁路运输和水路运输的重要节点,其装卸效率将影响集装箱海铁联运的整体效率.首先,对比分析了"船舶-列车"作业模式和"船舶-堆场-列车"作业模式的特点,并结合海铁联运港口实际作业情况提出了混合作业模式.然后,以轨道吊完工时间最短为目标构建混合整数规划模型,既考虑了班列和船舶的作业时...     

Application of a mixed fuzzy decision making and optimization programming model to the empty container allocation

Containerization transportation has been growing fast in the past few decades. International trades have been growing fast since the globalization of world economies intensified in the early 1990s. However, these international trades are typically imbalanced in terms of the numbers of import and export containers. As a result, the relocation of empty containers has become one of the important problems faced by liner shipping companies. In this paper, we consider the empty container allocation problem where we need to determine the optimal volume of empty containers at a port and to reposition empty containers between ports to meet exporters’ demand over time. We formulate this empty container allocation problem as a two-stage model: in stage one, we propose a fuzzy backorder quantity inventory decision making model for determining the optimal quantity of empty container at a port; whereas in stage two, an optimization mathematical programming network model is proposed for determining the optimal number of empty containers to be allocated between ports. The parameters such as the cost of loading container, cost of unloading container, leasing cost of empty container, cost of storing container, supplies, demands and ship capacities for empty containers are considered in this model. By taking advantages of the fuzzy decision making and the network structure, we show how a mixed fuzzy decision making and optimization programming model can be applied to solve the empty container allocation problem. The utilization of the proposed model is demonstrated with a case of trans-Pacific liner route in the real world. Six major container ports on the trans-Pacific route are considered in the case study, including the Port of Kaohsiung, the Port of Hong Kong, the Port of Keelung, the Port of Kobe, the Port of Yokohama and the Port of Los Angles. The results show that the proposed mixed fuzzy decision making and optimization programming model can be used to solve the empty container allocation problem well.     

A recursive model for static empty container allocation

Backlogged empty containers have gradually turned into a serious burden to shipping networks. Empty container allocation has become an urgent settlement issue for the container shipping industry on a global scale. Therefore, this paper proposes an improved immune algorithm based recursive model for optimizing static empty container allocation which integrates with the global maritime container shipping network. This model minimizes the operating and capital costs during container shipping considering 0–1 mixed-integer programming. So an immune algorithm procedure based on a special twodimensional chromosome encoding is proposed. Finally, computational experiments are performed to optimize a 10-port static empty container shipping system. The results indicate that the proposed recursive model for static empty container allocation is effective in making an optimal strategy for empty container allocation.     

集装箱海运空箱分派随机规划模型研究*

通过对海运集装箱空箱分派过程的仔细分析,在考虑需求不确定性的基础上引入了空箱运输能力的不确定性这一重要因素,建立了同时考虑供需平衡约束以及需求和空箱运输能力不确定性的空箱分派随机规划模型,并应用机会约束规划方法对模型求解.最后通过数值仿真,揭示了运输成本、租箱成本和存储成本等参数和空箱运输能力的不确定性对集装箱空箱分派策略的影响机制.     

Exact and approximate solutions of the container ship stowage problem

This paper deals with a stowage plan for containers in a container ship. Containers on board a container ship are placed in stacks, located in many bays. Since the access to the containers is only from the top of the stack, a common situation is that contianers designated for port J must be unloaded and reloaded at port I (before J) in order to access containers below them, designated for port I. This operation is called “shifting”. A container ship calling many ports, may encounter a large number of shifting operations, some of which can be avoided by efficient stowage planning. In general, the stowage plan must also take into account stability and strength requirements, as well as several other constraints on the placement of containers. In this paper we deal with stowage planning in order to minimize the number of shiftings, without considering stability constraints. First, a 0–1 binary linear programming formulating is presented that can find the optimal solution for stowage in a single rectangular bay of a vessel calling a given number of ports, assuming that the number of constainers to ship is known in advance. This model was successfully implemented using the GAMS software system. It was found, however, that finding the optimal solution using this model is quite limited, because of the large number of binary variables needed for the formulation. For this reason, several alternative heuristic algorithms were developed. The one presented here is based on a “reduced” transportation matrix. Containers with the same source and destination ports are stowed in full stacks as much as possible, and only the remaining containers are allocated by the binary linear programming model. This approach often allows the stowage planning of a much larger number of containers than using the exact formulation.     

Empty container repositioning strategy in intermodal transport with demand switching

In this paper, we study the empty container inventory repositioning problem with customer demand switching in intermodal transport. The objective of this article is to solve the empty container repositioning problem by contract coordination theory, and to improve the coordination of empty container management and the profit of each participant. We consider an intermodal transport system composed of the rail firm and the liner firm. First, we have considered the situation of no cooperation between the dry port and the seaport, and established a model where there is only the customer demand switching without the occurrence of empty container repositioning. Next, we consider the cooperation between the dry port and the seaport in the decentralized model and the centralized model, and set up the empty container repositioning models from the seaport to the dry port respectively. We analyse the optimal inventory level for the dry port and the seaport under different models, and the effect of the repositioning price on the optimal inventory level. We then apply the contract coordination theory to the empty container inventory repositioning problem. We propose an inventory coordination strategy based on a revenue sharing contract and coordinate the intermodal transport system by choosing the appropriate contract parameters. The results of the study show that under the guidance of the seaport, the revenue sharing contract can achieve a win-win situation for the dry port and the seaport.     

基于($D,U$)控制策略的港口群空箱存储与调运联合优化

针对区域港口群内陆公共腹地的空箱供需状况,构建多港口、多周期空箱存储与调运联合优化混合整数规划模型,利用马尔科夫决策过程与动态规划相结合的方法,在(D,U)库存控制策略下对港口群内各港口的空箱库存保有量区间进行动态优化,以此为基础对港口群公共腹地和各港口间的空箱调运方案进行优化,并以辽宁沿海港口群-----东北腹地为对象进行实证分析.实验结果表明,(D,U)控制策略下的空箱调运能够为船公司节省15.22%的总成本.选取公共腹地数量、公共腹地和港口空箱需求量、单位租箱成本以及单位库存成本进行灵敏度分析,进而验证(D,U)控制策略能够削弱船公司在外界环境发生变化时受到的影响.     

铁路集装箱物流中心系统建模与仿真分析

铁路集装箱物流中心作业系统是复杂的随机系统,难以用数学模型准确描述。采用系统仿真的方法,依据集装箱物流中心的作业流程,构建基于eM-Plant的铁路集装箱物流中心整体作业模型。通过仿真实验,研究到站集装箱列车所载箱箱型比例、外卡到站时间间隔和内卡数量等模型参数对集装箱物流中心作业性能的影响。仿真结果表明集装箱列车所载箱箱型比例为6∶1∶3时装卸设备利用率最高,外卡在到站时间间隔超过8 min时无需等待,内卡数为5~7时辅助中转箱转运作业时间最少。     

Optimal control of container cranes

A dynamical model of container cranes is derived by using Lagrange's equation. When a ship is loaded or unloaded with containers, the total motion of the container load is divided into five fundamental sections. For each fundamental type of motion, the optimal control is calculated such that the corresponding trajectory satisfies the specified boundary conditions and that the swing of the container load during the transfer is minimized. A new algorithm which is employed for computing the optimal control is explained in detail. Some results of numerical computation are also shown.     

A genetic algorithm to solve the storage space allocation problem in a container terminal

In this paper, an efficient genetic algorithm (GA) is presented to solve an extended storage space allocation problem (SSAP) in a container terminal. The SSAP is defined as the temporary allocation of the inbound/outbound containers to the storage blocks at each time period with aim of balancing the workload between blocks in order to minimize the storage/retrieval times of containers. An extended version of a SSAP proposed in the literature is considered in this paper in which the type of container affects on making the decision on the allocation of containers to the blocks. In real-world cases, there are different types (as well as different sizes) of containers consisting of several different goods such as regular, empty and refrigerated containers. The extended SSAP is solved by an efficient GA for real-sized instances. Because of existing the several equality constraints in the extended model, the implementation of the GA in order to quick and facilitate achieve to the feasible solutions is one of the outstanding advantages of this paper. The performance of the extended model and proposed GA is verified by a number of numerical examples.