Analysis and optimal design of discrete order picking technologies along a line

Order picking accounts for most of the operating expense of a typical distribution center, and thus is often considered the most critical function of a supply chain. In discrete order picking a single worker walks to pick all the items necessary to fulfill a single customer order. Discrete order picking is common not only because of its simplicity and reliability, but also because of its ability to pick orders quickly upon receipt, and thus is commonly used by e‐commerce operations. There are two primary ways to reduce the cost (walking distance required) of the order picking system. First is through the use of technology—conveyor systems and/or the ability to transmit order information to pickers via mobile units. Second is through the design—where best to locate depots (where workers receive pick lists and deposit completed orders) and how best to lay out the product. We build a stochastic model to compare three configurations of different technology requirements: single‐depot, dual‐depot, and no‐depot. For each configuration we explore the optimal design. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Capacitated warehouse location model with risk pooling

In this article, we introduce the capacitated warehouse location model with risk pooling (CLMRP), which captures the interdependence between capacity issues and the inventory management at the warehouses. The CLMRP models a logistics system in which a single plant ships one type of product to a set of retailers, each with an uncertain demand. Warehouses serve as the direct intermediary between the plant and the retailers for the shipment of the product and also retain safety stock to provide appropriate service levels to the retailers. The CLMRP minimizes the sum of the fixed facility location, transportation, and inventory carrying costs. The model simultaneously determines warehouse locations, shipment sizes from the plant to the warehouses, the working inventory, and safety stock levels at the warehouses and the assignment of retailers to the warehouses. The costs at each warehouse exhibit initially economies of scale and then an exponential increase due to the capacity limitations. We show that this problem can be formulated as a nonlinear integer program in which the objective function is neither concave nor convex. A Lagrangian relaxation solution algorithm is proposed. The Lagrangian subproblem is also a nonlinear integer program. An efficient algorithm is developed for the linear relaxation of this subproblem. The Lagrangian relaxation algorithm provides near‐optimal solutions with reasonable computational requirements for large problem instances. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

基于遗传算法的虚拟物流联合库存控制研究

针对随机需求条件下的虚拟物流库存控制问题进行了深入研究，提出了一种新的联合库存控制策略——（T，S，s）策略，建立了相应的库存成本模型，并构造遗传算法对模型进行求解。结果分析表明，所提出的（T，S，S）联合库存控制策略是有效的。     

面向AL的战略级仓库备件供应优化方法

针对维修备件供应保障费用较高、管理难度较大等问题,借助自主式保障(AL)理念设计了面向AL的维修备件调度与供应优化框架,提出面向AL的战略级仓库维修备件供应优化思路。在此基础上,为了解决战略级仓库备件供应路线规划不科学、弥补半定量经验方法不足的情况,建立了带混合时间窗的多供应地——多需求地维修备件供应路线优化模型,设计了求解模型的GA-SA混合算法。最后运用算例进行了说明。     

Scheduling combat logistics force replenishments at sea for the US Navy

The Replenishment at Sea Planner (RASP) is saving the U.S. Navy millions of dollars a year by reducing fuel consumption of its Combat Logistics Force (CLF). CLF shuttle supply ships deploy from ports to rendezvous with underway U.S. combatants and those of coalition partners. The overwhelming commodity transferred is fuel, ship‐to‐ship by hoses, while other important packaged goods and spare parts are high‐lined, or helicoptered between ships. The U.S. Navy is organized in large areas of responsibility called numbered fleets, and within each of these a scheduler must promulgate a daily forecast of CLF shuttle operations. The operational planning horizon extends out several weeks, or as far into the future as we can forecast demand. We solve RASP with integer linear optimization and a purpose‐built heuristic. RASP plans Replenishment‐at‐Sea (RAS) events with 4‐hour (Navy watch) time fidelity. For five years, RASP has served two purposes: (1) it helps schedulers generate a daily schedule and animates it using Google Earth, and (2) it automates reports command‐to‐ship messages that are essential to keep this complex logistics system operating.     

基于改进SLP的军事物流基地设施平面布局研究

由于传统SLP方法的不足,在解决设施较多的军事物流基地布局问题上面临较大困难。为解决此问题,提出了改进SLP方法,以军事物流基地设施间综合相互关系为基础,构建平面布局模型,并确定目标函数和主要约束条件。随后对模型的求解进行遗传算法设计,并运用Matlab编程实现模型的求解,从而得出平面布局的最优解。最后以最优解为基础,结合限制条件进行修正,完成军事物流基地设施平面布局设计。     

大空间建筑火灾扑救对策及组织保障探讨

在各类火灾扑救过程中,大空间建筑火灾的扑救是最常见也是最难扑救的一种,如何成功有效地扑救此类火灾是火灾扑救技战术的一个重要而现实的课题,就大空间建筑火灾的特点和攻防对策进行了大胆探讨。     

战术数据链发展现状及其对后勤信息化建设的启示

为推动信息化战争条件下后勤保障模式转变,加快后勤信息化建设,在简要介绍战术数据链相关概念及其发展现状的基础上,通过对国内外战术数据链发展现状的分析,重点论述了其对我军后勤信息化建设的启示,分析了数据链应在后勤信息化建设中发挥的重要作用及建设我军后方勤务数据链需要注意的问题.最后,从软、硬件构成要素和报文标准3方面给出了...     

增材制造技术在军事物流中的应用研究

增材制造技术是一种新型的制造技术,现已被应用到了航空航天、汽车工业和军事等诸多行业领域。作为军事领域的重要组成部分,军事物流与增材制造技术通过军用物资这一共同的作用对象为纽带存在着天然的联系。遗憾的是,目前增材制造技术在军事领域的应用范围还比较局限,有关军事物流的应用更是少见。为有效推动增材制造技术在军事物流中的应用实践,本文首先从装备研制、装备维修、医疗保障和工程保障四个方面归纳总结了增材制造技术的军事应用现状;在此基础上,研究探讨了增材制造技术在军事物流中的两种应用模式,即物资储备和伴随保障;最后,从思想认识、经费投入、理论研究、应用试点以及人才储备五个方面提出了增材制造技术的军事物流应用对策建议。     

基于物链网的军事供应链管理研究

现代化军事供应链管理是实现智慧军事物流的必要手段,智能军事供应链管理离不开物联网、区块链、云计算、人工智能等高新技术的支撑。随着物联网与区块链技术的发展,研究两者深度融合的物链网应用对提高军事供应链管理具有重要意义。本文通过分析军事供应连管理特点及需求分析总结出军事供应链管理具有内外区分、网系异构、平战结合等特点,应用物联网与区块链融合可直击军事供应链痛点问题,为解决军事供应链管理智能化发展、快速响应、共识共享、安全保密等需求提供新思路;同时,对物链网应用的技术融合化、链条联盟化、连接标准化、计算边缘化展开研究,提出军事供应链在可追溯与可视化、供应链协同以及物流流程优化等方面的智能管理,以期为物链网在军事供应链管理的应用提供一定参考。