Simultaneous control of vehicle routing and inventory for dynamic inbound supply chain

This paper investigates inbound logistics for an OEM (Original Equipment Manufacturing) manufacturer, who aims at short production time and JIT policy. In such a case, it can be argued that the inbound vehicle routing schedule should be combined with incoming parts inventory control. In this paper, we propose a simultaneous control method of combining vehicle scheduling and inventory control for such dynamic inbound logistics. For the transportation control, a vehicle routing system, in which delivery jobs are made with shipments of one supplier, is proposed to generate a vehicle routes plan by considering production start time, travel time, waiting time, and loading/unloading time. To evaluate the performance of the generated vehicle routing plan, a goal model is also developed by considering vehicle operating cost, stock level exceeding penalty, and transportation efficiency. A generated vehicle routing plan can be rejected when the stock level is over the capacity and an appropriate number of vehicles for its manufacturing environment can be determined. Using real data from an LCD firm, a simulation study is conducted. The simulation results indicate that the simultaneous control approach requires fewer vehicles than the existing system and shows better efficiency of transportation. This method can also be used to determine the appropriate incoming part inventory level or the number of vehicles required in dynamic inbound logistics.     

一种集成最后一公里的四方物流网络设计问题启发式算法

最后一公里分销网络可以帮助企业达成高响应性的供应链管理目标,集成最后一公里四方物流网络设计问题成为网络设计的一个重要研究方向.解决该问题需要对分销中心的位置,三方物流的选择、分配以及其车辆路径规划进行决策.在满足车辆路径规划、流守恒等约束条件下,以最小化网络构建费用为目标建立混合整数规划模型.由于该问题的NP-难特性,...     

不对称信息下第四方物流配送时间契约设计

第四方物流与第三方物流构成委托代理关系, 信息不对称与风险规避为第四方物流配送时间契约设计带来了难题. 对此, 分别在集中式决策、对称成本信息和不对称成本信息3 种情景下进行研究, 给出最优配送时间契约, 并对最优契约结果进行分析. 实验结果表明: 最优契约能够实现对第三方物流的激励, 有效地管理物流配送时间; 同时, 不对称信息与风险规避均会降低系统表现. 数值实验说明了不对称信息与风险规避对最优配送时间契约的影响.

     

不同任务结构下外包物流配送时间契约设计

外包物流的快速发展带来了新的契约设计问题, 研究不同任务结构下的外包物流配送时间契约设计具有重要意义. 首先, 从第四方物流的视角出发, 考虑外包物流配送时间契约, 分别针对串行任务结构和并行任务结构, 建立委托代理数学模型; 然后, 给出最优契约的确定方法, 并对最优契约结果进行分析; 最后, 通过数值实验验证了两种不同任务结构下配送时间契约设计方法的有效性.

     

第三方物流的多维数据模型

现有第三方物流企业的管理信息系统普遍采用传统的关系型数据库.随着大量关系数据的聚集,借助关系模型分析数据已明显不足.基于此,提出了采用数据仓库技术建立数据中心的解决方案,为企业决策层提供所需的数据环境.此外,按照维度建模方法,为第三方物流运输管理提供了具体的多维数据模型和应用分析.     

RETRACTED ARTICLE: Hierarchical evaluation algorithm of logistics carrying capacity based on transfer learning in multimedia environment

In order to measure and enhance the carrying capacity of regional logistics system scientifically and give full play to the efficiency of regional logistics system, based on the perspective of sustainable development, this paper analyzes the network topology structure of regional logistics system. Combining the component elements and operation flow of regional logistics system, we take link line, operation capacity and energy environment as constraint conditions, and construct the measurement model of regional logistics system carrying capacity. The integrated management of logistics requires systematic integration of various modes of transportation, such as highway transportation, water transportation, rail transportation and air transportation, as well as the network of key nodes and their network. Therefore, we need to solve the different transportation models and the nodal carrying capacity calculation methods that constitute the logistics system. Therefore, this paper analyzes the connotation, various transportation mode and port capacity related to the concept of research ideas, research tools and methods, the related calculation formula, traffic flow as the main line to construct different modes of transport carrying capacity between the inner link, and the bearing capacity formula of each transport mode into a unified unit, the transportation mode of coordinated development that is the basis of the overall optimization and decision of logistics system.

     

汽车零部件Milk-run车辆调度优化模型和算法

为了寻求汽车零部件采用循环取货时车辆的最优路径,提出将每个供应商零部件循环、分批提取使车辆尽可能满载的建模思路,建立具有车辆容积、车辆到达时间窗、供应商供货动态时间窗、车辆最大行程约束的车辆调度优化模型,设计了用于求解该模型的改进启发式节约算法。最后通过算例验证了多重约束模型及算法的有效性。     

协商式的物流联盟运输规划模型优化研究

通过分析一次完整的物流联盟企业项目型物流配送过程,提出物流联盟规划问题的两阶段解决方案。首先,针对当前大型物流配送系统的现状,采用实例化路径视图的策略,预先计算和存储可行路径,给出相应算法。其次,在信息不完备情况下,采用基于协商的Agent技术优化可行路径。实验证明：在不完全信息下,解决方案能求得在指定时间约束下的最优成本方案。     

基于单据驱动的物流管理系统的设计与实现

论文结合为某机械制造集团开发的物流管理系统,提出了基于单据驱动的物流管理系统解决方案,并详细阐述了其基本思想和系统实现方法。方案以单据流转为中心,结合企业物流管理原理,有效集成了企业的相关资源,保证了企业整个物流过程的畅通和时效,真正实现了企业的物流、资金流和信息流三流合一的目标。     

基于数据驱动的物资储检配一体化系统研究和应用

针对现有电力物资仓库管理和运营多基于人工作业方式进行,工作内容繁杂,管理内容多样,数据处理量大,难以进行有效的归并和融合分析。再加上物资配送基本以需求部门自提为主,调配难度大;缺乏信息共享机制,无法对规定时期内的物资进行及时质检分析,造成物资供应链管理支撑不足的问题。本文将仓储“储、检、配”多源事件数据进行融合分析。首先识别并解析数据源实体,对于存在的瑕疵数据进行基于知识图谱的修复和整理;接下来结合仓储作业一体化的趋势特点,对仓储运行数据融合多级入出比控制模型,实时动态平衡与调整仓库库存;最后提出基于实时调度配送模型,调度各级入出库数据进行求解优化。经过测试使用,大大提高了仓储信息交互效率,进一步改善了物流的配送效率,节约管理运营成本,提高竞争力。     

考虑交通时变特性的城乡快递无人机配送优化研究

针对农村快递网点运营成本高、网点建设滞后导致的电商物流配送成本高问题,提出了城乡客运班车+无人机的快递配送模式。在考虑了配送过程中路网交通的时变特性的情况下,以无人机—车辆配送系统总成本最小为优化目标,建立了时变网络下带时间窗的无人机—车辆路径问题（TDVRPDTW）模型,并提出一个由基于最近邻思想的改进CW算法和动态规划启发式算法构成的两阶段启发式算法来求解TDVRPDTW。最后,通过算例求解验证构建模型的合理性和求解算法的有效性,为制定农村物流配送的城乡客运班车+无人机快递配送方案提供决策支持。     

Optimizing truck sequencing and truck dock assignment in a cross docking system

Cross docking plays a very importation role in supply chain management. The efficiency of cross docking will influence the lead time, inventory level and response time to the customer. This research aims to improve the efficiency of multi-door cross docking by optimizing both inbound and outbound truck sequencing and both inbound and outbound truck dock assignment. The objective is to minimize the makespan. The problem is new in the literature and no previous formulation of the problem can be found. In order to optimize the problem, a model for calculating the makespan is proposed. When given a sequence of all inbound and outbound trucks, the calculation model can assign all inbound and outbound trucks to all inbound and outbound doors based on first come first served and then calculate the makespan. The proposed makespan calculation model is then integrated with a variable neighborhood search (VNS) which can optimize the sequence of all inbound and outbound trucks. Four simulated Annealing (SA) algorithms are adopted for comparison. The experimental results show the proposed VNS provides 8.23–40.97% improvement over the solution generated randomly. Although it does not provide the best result for all problems when compared with SA algorithms, it provides robust results within a reasonable time. Thus the proposed method is efficient and effective in solving cross docking operation problems.     

Determine the optimal carrier selection for a logistics network based on multi-commodity reliability criterion

From the perspective of supply chain management, the selected carrier plays an important role in freight delivery. This article proposes a new criterion of multi-commodity reliability and optimises the carrier selection based on such a criterion for logistics networks with routes and nodes, over which multiple commodities are delivered. Carrier selection concerns the selection of exactly one carrier to deliver freight on each route. The capacity of each carrier has several available values associated with a probability distribution, since some of a carrier's capacity may be reserved for various orders. Therefore, the logistics network, given any carrier selection, is a multi-commodity multi-state logistics network. Multi-commodity reliability is defined as a probability that the logistics network can satisfy a customer's demand for various commodities, and is a performance indicator for freight delivery. To solve this problem, this study proposes an optimisation algorithm that integrates genetic algorithm, minimal paths and Recursive Sum of Disjoint Products. A practical example in which multi-sized LCD monitors are delivered from China to Germany is considered to illustrate the solution procedure.     

基于RGBD的箱体尺寸测量与包装优化

针对国内物流行业与国外相比包装耗材浪费严重，对包装优化有着巨大需求的现状，提出一种新的装箱方案，并设计一种基于遗传算法的包装优化方法，目标是从已有的包装规格中找出表面积最小并能容纳所需货物箱体的包装规格。本包装优化方法以货物的摆放序列和摆放朝向作为遗传编码，配合空间分割规则寻找包装规格的最优解；同时，考虑到传统激光扫描测量设备成本高昂，为了适应国内仓储管理模式，给包装优化提供货物尺寸信息，本文还设计一种基于RGBD的箱体尺寸测量方法。实验结果表明，本文方法能够快速精确地测量货物尺寸并选择合适的包装规格。     

基于混合蚁群算法的物流配送路径优化

基本蚁群算法在优化过程中存在搜索时间长、易陷入局部最优解的缺点.研究构造了一种基于蚁群算法的混合算法,利用蚁群算法首先求出问题的基本可行解,采用遗传变异中的单亲逆转算子进行再次优化,求得问题最优解.对物流配送路径优化的仿真试验表明,相对于基本蚁群算法和遗传算法,混合算法的优化质量和效率更优.     

基于RFID和ZigBee的快递管理系统

随着电子商务的不断发展,校园快递业务量迅速增长,传统快递取件模式货物出入库效率低,物流环节的人工成本高.据此,本文提出了一种基于RFID和ZigBee的快递管理系统,利用ZigBee网络来进行组网,利用RFID技术来实现自动化管理快递,将RFID标签贴在每个货物的包装,在驿站货架上设置固定式读写器,来获取货物位置、编号等信息,用户根据手机收到的二维码自主寻找货物,在出口闸机通道扫描快递标签及手机上的二维码来进行匹配,完成自主取货,提高快递出入库效率.     

Meta-heuristics implementation for scheduling of trucks in a cross-docking system with temporary storage

Cross-docking is an approach in inventory management which can reduce inventories, lead times and customer response time. In this strategy, products and shipments are unloaded from inbound trucks, sorted and categorized based on their characteristics, moved and loaded onto outbound trucks for delivery to demand points in a distribution network. The important fact is that, the items are stored in the inventory for a period which is primarily less than the actual time allocated to keep these items in a typical warehouse. Therefore, total cost and space requirement for inventory can be cut down. One of the most important targets in such systems is to establish coordination between the performance of inbound and outbound trucks in that these trucks can be scheduled, and the product items can be allocated to trucks effectively. This paper addresses some meta-heuristics to find the best sequence of inbound and outbound trucks, so that the objective, minimizing the total operation time called makespan, can be satisfied. Furthermore, not only the efficiency and capability of the algorithms’ parameters are assessed and analyzed by some performance measures, but also these meta-heuristics are compared with each other in order to find out the set of homogeneous algorithms among all proposed algorithms. By this analysis, it can be shown that the suitability of these meta-heuristics is quite sensible especially for the cross-docking systems with large sizes in which a high volume of inbound or outbound trucks transmit the product items.     

考虑多种运输方式的整车物流服务供应链订单分配问题

针对整车物流服务供应链的订单分配问题，提出了考虑多种运输方式的双层订单分配模型。首先，考虑到运输方式会影响运输成本、客户的准时送达要求等因素，建立以准时送达和最小化物流采购成本为目标的双层规划模型；其次，设计启发式算法（HA）确定各运输方式的任务量；然后，借助混合蛙跳算法（SFLA）求解各功能物流服务提供商间各运输方式的任务量分配；最后，通过不同规模的算例与遗传算法（GA）、粒子群算法（PSO）、蚁群算法（ACO）等进行求解对比。算例结果表明，与原有的成本438万元相比，所提模型得到显著优化的421万元，说明所构建模型的订单分配方案能够更有效解决整车物流的订单分配问题。实验对比表明，较传统智能算法（GA、PSO、ACO）的求解结果，两阶段的HA-SFLA算法能更快得出显著优化的结果，说明HA-SFLA算法能更好地求解考虑运输方式的双层订单分配规划模型。在满足客户送达时间要求的同时，考虑运输方式的双层订单分配模型及算法显著降低物流成本，促进物流集成商为获取更多利益而在订单分配阶段考虑运输方式。     

Using telephone call rates and nurse-to-patient ratios as measures of resilient performance under high patient flow conditions

Patient admissions, discharges, and transfers are high work demand activities that have been associated with 30-day readmissions and increased patient mortality. Most mitigation strategies target peak demand, but variable demand may be more significant. Self-organizing holarchic open systems (SOHOs) and resilience engineering frameworks may explain system behavior, but a few quantitative studies of resilient organizational performance have been published. We used three measures to explore SOHO and resilience engineering constructs. We collected hourly data over 2 years, from five inter-related units in a cardiovascular disease division of a metropolitan teaching hospital. Our results show that information flows (inbound, outbound, answered, and unanswered telephone calls) representing anticipatory management are related to patient flows (patient admissions discharges and transfers) and nurse-staffing levels (nurse-to-patient ratios). We also found overall system stability despite high patient flow effects in lower level units. Unexpectedly, the time to recovery from high patient flow events lasted up to 7 days. We conclude that constructs proposed by resilience engineering can be quantified using simple measures collated within routine operations. The application of nonlinear statistical analyses can uncover important insights about resilient performance that may assist managers in better preparing for managing and recovering from unexpected variation in patient flow.

     

Solution method for the location planning problem of logistics park with variable capacity

In this paper we study a logistics park location planning problem in which the capacity of the logistics park is determined by the sectors used to establish it in an open site. Since the size of each sector is not necessarily the same in every potential site, the capacity of the logistics park is thus variable, which makes this problem different from the traditional location problems in which the capacity of each facility is fixed. The task of this problem is to determine the location of the logistics parks, the sectors to be used to establish the logistics park in each open site, and the allocation of customers to the established logistics parks so as to minimize the total costs for establishing the logistics parks and supplying the demands of customers. The size mode is introduced to deal with the nonlinear establishment cost function and consequently this problem is formulated as an integer linear programming (ILP) model. Since CPLEX can only solve the ILP model with small-size problems, a tabu search (TS) hybrid with filter and fan (F&F) is presented to obtain near optimal solutions. In the hybrid algorithm, the TS is used to improve the solution by changing the allocation of customers to open sites while the F&F is used to further improve the solution by adjusting the status of sites (i.e., open or closed). In addition, an elite solution pool is constructed to store good solutions found in the searching history. Whenever the hybrid algorithm is trapped in local minima, a new start solution will be generated from the elite pool so as to improve the search diversity. To evaluate the performance of the proposed hybrid TS method, the column generation (CG) method with an acceleration strategy is developed to provide tight lower bounds. Computational results showed that the proposed hybrid algorithm can obtain optimal solutions for most of the small size problems and satisfactory near-optimal solutions with comparison to lower bounds for large size problems.