具有时变运输时间的JIT系统批量决策

本文的研究对象是由制造商、配送中心和零售商组成的多级供应链系统,其中零售商要求制造商为其提供短时间间隔、小批量的JIT配送。研究内容为在时变运输时间影响下的供应链系统批量决策问题。在实际运输时间数据的基础上建立了时变运输时间的函数,并以此构建了系统的总成本函数,并在相关文献研究的基础上采用新的更为有效搜索规则进行了求解。根据求解规则,采用ActiveX自动化技术将Matlab的数值计算功能嵌入Visual Basic的集成开发环境中,开发了对应的决策支持系统。最后进行了敏感性分析并提供了低运作成本的决策支持方案。     

B2C电子商务环境下订单拣选与配送联合调度优化

如何在顾客下单后协调好拣选和配送环节,在最短的时间、以较低的成本将商品从货架上拣出、打包后配送到顾客手中,已成为B2C电子商务物流管理中亟待解决的问题。本文尝试以最小化订单履行时间为目标,构建非线性拣选与配送联合调度模型,以解决订单拣选顺序、拣选作业方式、车辆行驶线路等联合决策。为求解此NP难问题,设计了三阶段启发式算法：首先采用“聚类-路径优化”思想,依据顾客位置进行配送方案确认;然后采用基于相似度聚类的订单分批规则对每条配送线路的订单进行分批合并;最后调整拣选任务与配送线路顺序。通过数据实验对模型进行验证,并与传统拣选与配送分开优化的结果进行对比。结果表明,三阶段算法能够有效缩短订单完成时间、降低配送车辆等待时间、改善配送资源利用率。     

考虑第三方物流竞争的第四方物流运输与库存外包决策

第四方物流在物流外包中的主导地位和第三方物流在提供服务时基于配送频率的竞争对物流外包产生重要影响。针对这一问题,本文建立基于价格、配送频率和需求分配比例的三阶段非合作动态决策模型和库存运输联合优化模型(ITIO)来分析4PL主导的业务外包和3PL之间的竞争,通过对比两个模型来分析决策权对个体和系统绩效的影响,并用算例验证了文章的结论。研究表明,在3PL同质且需求分配比例为0.5时,三阶段非合作动态决策模型的配送频率比ITIO最优值小29%,库存持有成本比ITIO最优值高41%,物流配送成本比ITIO最优值小21%,总成本比ITIO最优值大9%。库存运输联合优化模型虽然具有一定成本优势,但是其过分强调协调不利于3PL之间的竞争和提高。     

基于JIT的同步配送在汽车企业的研究应用

本文对长安铃木原来实施的JIT配送管理系统进行研究,分析长安铃木JIT配送流程存在的问题.结合长安铃木配送的实际情况,构建同步配送系统并成功实施,降低了零件库存,提高了生产效率.     

大数据驱动的决策范式转变——以个性化O2O即时物流调度为例

大数据环境下传统的决策范式正转变为基于数据的决策范式，本文以O2O即时服务这种新型商业模式为情景，研究大数据驱动的新决策范式下的O2O即时物流调度模型.本文跨域融合物流部门、其他运营部门以及外部环境信息构成全景式数据，同时放宽传统决策范式的经典假设，实现从无差异化配送时间到个性化配送时间的转变，以及需求服从先验分布到考虑未来需求时空属性的转变.本文融合机器学习和运筹优化方法，实现新决策范式下的O2O即时物流调度模型.在预测层面，构建个性化众包配送时间预测模型和基于订单集时空相似性的需求场景预测算法；在决策层面，同时考虑个性化预测模型的点估计及其不确定性，并考虑未来订单集的时空分布，构建考虑预测不确定性的调度模型，同时设计同步预测和决策算法求解.本文与中国主流的O2O商超平台合作，通过基于真实数据的模拟仿真，验证了新决策范式下的O2O即时物流调度模型的可行性和有效性.相较于传统的决策范式，本文提出的模型能实现更精准的供需匹配，降低延误订单数、平均配送时间和配送成本.     

3PL参与的时变需求变质品三级供应链模型

随着现代物流业的发展,企业将一些业务如运输等外包已经成为参与当今市场竞争的一种手段和趋势,因此考虑包含第三方物流服务提供商（3PL）的供应链更具有现实和理论意义。但是现有文献很少考虑3PL对包含时间因素的变质品供应链模型的影响。基于此,本文建立了一个包含3PL的时变需求变质品三级供应链模型,并运用动态博弈理论求解了该模型的分散式下的均衡解。研究表明与制造商单独承担运输费用相比,由3PL承担运输费用使得产品的订货周期缩短,订货量减少。通过对比分散式决策和集中式决策下的最优解,研究发现考虑系统总体利润情况下,集中式决策的方式不能使该供应链达到协调。最后给出算例验证结论的正确性。     

平行机作业环境下的订单分配与排序

针对一类平行机作业环境下的订单分配与排序问题,从整体的角度协同优化供应链中的订单分配、生产调度和分批运输调度。以完成所有订单的总订货提前期与生产运输总成本的加权和最小化为目标,构建了问题的数学模型。将基于向量组编码结构的禁忌搜索算法与基于动态规划方法的启发式算法相结合,设计了一种混合优化算法以求解问题。对不同策略和不同算法进行比较,数据实验结果显示了订单分配与排序策略的优越性及所提算法的有效性。     

考虑完成期限的电子商务在线订单分批模型及算法

在电子商务在线订单拣选系统中,订单到达时间和订购商品等信息未知。针对拣选设备容量、员工人数等资源有限约束情况,研究在何时、对多少订单进行分批优化,以保证在订单完成期限前以最短的时间拣出最多的订单。构建考虑订单完成期限的在线订单分批混合整数规划模型,以最小化平均有效订单服务时间,采用改进的固定时间窗订单分批启发式规则求解模型,定义剩余操作时间在[前置时间,配送准备时间]内的订单为紧急订单,构建综合考虑紧急程度和相似度因素的在线订单分批算法。采用某配送中心14：00～18：00时间段内以泊松分布（λ＝17）随机生成的订单进行数据实验,将实验结果与传统固定时间窗在线订单分批算法进行比较。研究结果表明,考虑完成期限时,系统拣选配送的订单数量更多,总服务时间和平均有效订单服务时间更短,且出现延迟订单的数量更少,延迟时间更短。拣选员工人数的增多在不同程度上提高配送率,且考虑完成期限时,配送率提高幅度要大于传统算法;但随着人数的增加,配送率的提高幅度呈降低趋势。     

基于决策支持系统运行结构的医药调拨配送问题研究

为满足医药公司提高药品调拨配送效率和降低成本的要求,本研究构建了医药调拨配送决策支持系统.该系统通过药品订单汇总、分配方案制订和运输方案确定、结果汇总等过程,给出药品订单分配和运输的优化方案,最大限度地提高了调拨配送过程的灵活性、高效性和合理性,为药品调拨配送提供了有效的决策支持.     

易变质产品在带运输时间的二级供应链中的订购策略研究

研究了带运输时间的易变质产品的二级供应链库存模型。在有限计划期内,为补充下游分销商发出的订单,上游制造商以一定的生产速率进行生产。由于产品运输给分销商时需要花费时间与成本,在开始一段时间内分销商的订单得不到及时补充,只有当制造商的库存量达到最大时,才将产品运输给分销商。目标就是确定最优订购策略使得整个系统的总成本最小。通过分析成本函数的特点,证明了2种特殊情形下最优解的存在及唯一性。最后通过算例验证了最优策略的有效性。     

考虑交货因素的热轧无缝钢管订单排程模型与算法

无缝钢管的市场需求具有多品种、小批量的特点，为了在满足客户需求的同时保证高效连续化生产，文章在满足生产工艺特征的基础上将配送地址和交货期等合同因素引入热轧无缝钢管订单排程问题中，建立了以适期交货、订单集中生产配送和最小化机器设备调整为优化目标的订单排程优化模型，并设计了两阶段求解算法：首先，以订单交货期与配送地址差异最小为目标，基于凝聚策略设计了订单聚类算法，将具有相同工艺约束、相似合同要求的订单进行聚类，并形成初始轧制计划；然后，以设备调整和提前/拖期最小为目标，设计混合变邻域搜索算法，对初始轧制批次进行排程优化。基于实际订单数据的实验结果表明，模型和算法对问题的描述和求解是可行有效的。     

Information quality deficiencies in delivery schedules and their impact on production scheduling

The purpose of this paper is to explore how different delivery schedule characteristics affect the quality of shared delivery schedule information and, in turn, how deficiencies in quality affect a supplier’s production scheduling process. It describes a case study conducted in the Swedish automotive industry involving a supplier that operates as the first-, second- and third-tier supplier to an original equipment manufacturer. The study reveals how four delivery schedule characteristics – namely, receiving frequency, planning period, frozen period and demand variation – create information quality (IQ) deficiencies in five dimensions of IQ: completeness, conciseness, reliability, timeliness and credibility. At the same time, it demonstrates how such deficiencies affect the supplier’s production scheduling process by requiring additional rescheduling, reworking and follow-up activities as well as additional capacity problems, safety time, safety stock and backlogs. In effect, the paper extends previous IQ-related research by considering IQ in delivery schedules.     

新零售模式下在线零售商融资均衡与协调策略研究

针对电商平台主导的新零售模式,考虑一个在线零售商和一个第三方物流企业（3PL）组成的二级供应链中,银行或3PL企业为面临资金约束的在线零售商提供融资,建立三者之间的Stackelberg博弈模型。研究发现：当在线零售商选择积极型3PL企业融资时,其订购量和系统各参与成员的期望利润更优;当满足协调条件时,若初始资金为常数,3PL企业的利率与运输费之间存在线性递减关系;当满足弱协调条件时,针对不同的初始资金,积极型3PL企业可以设计出多种融资协调合同;资金充足的在线零售商会更偏向协调的积极型3PL企业融资,而不是拒绝任何外部融资。     

Integrated Order Scheduling and Packing

We consider an integrated production–distribution scheduling model in a make‐to‐order supply chain consisting of one supplier and one customer. The supplier receives a set of orders from the customer at the beginning of a planning horizon. The supplier needs to process all the orders at a single production line, pack the completed orders to form delivery batches, and deliver the batches to the customer. Each order has a weight, and the total weight of the orders packed in a batch must not exceed the capacity of the delivery batch. Each delivery batch incurs a fixed distribution cost. The problem is to find jointly a schedule for order processing and a way of packing completed orders to form delivery batches such that the total distribution cost (or equivalently, the number of delivery batches) is minimized subject to the constraint that a given customer service level is guaranteed. We consider two customer service constraints—meeting the given deadlines of the orders; or requiring the average delivery lead time of the orders to be within a given threshold. Several problems of the model with each of those constraints are considered. We clarify the complexity of each problem and develop fast heuristics for the NP‐hard problems and analyze their worst‐case performance bounds. Our computational results indicate that all the heuristics are capable of generating near optimal solutions quickly for the respective problems.     

考虑公平偏好的委托模式融通仓银行对3PL激励

第三方物流（Third party logistics,3PL）努力工作和积极参与是融通仓有效运作的重要因素,因此促使其努力工作是一个非常重要的问题。本文在传统委托代理模型中加入“公平偏好”因素,并从是否考虑“公平偏好”因素两个方面,研究银行对3PL的激励问题。研究发现,考虑“公平偏好”因素后。银行给3PL的固定报酬高于传统委托代理模型中最优固定支付时,3PL会在最优努力程度上再增加一定数量的额外努力以回报银行的善意,且3PL“公平偏好”行为越强,增加的努力数量就越多,从而使银行收益高于传统委托代理模型中3PL选择最优努力水平时的收益。本文意义在于银行可以根据3PL“公平偏好”的强弱,合理设计报酬机制,以进一步增加自身收益。     

Coordinated scheduling of production and delivery stages with stage-dependent inventory holding costs

This paper considers a problem of integrated decision-making for job scheduling and delivery batching wherein different inventory holding costs between production and delivery stages are allowed. In the problem, jobs are processed on a facility at a production stage and then delivered at the subsequent delivery stage by a capacitated vehicle. The objective is to find the coordinated schedule of production and delivery that minimizes the total cost of the associated WIP inventory, finished product inventory and delivery, where both the inventory costs are characterized in terms of the weighted flow-time and the delivery cost is proportional to the required number of delivery batches. It is proved that the problem is NP-hard in the strong sense. Thereupon, three heuristic algorithms are derived. Some restricted cases are also characterized as being solvable in polynomial time. Numerical experiments are conducted to evaluate the performance of the derived heuristic algorithms.     

Improved approximation algorithms for non-preemptive multiprocessor scheduling with testing

Multiprocessor scheduling, also called scheduling on parallel identical machines to minimize the makespan, is a classic optimization problem which has been extensively studied. Scheduling with testing is an online variant, where the processing time of a job is revealed by an extra test operation, otherwise the job has to be executed for a given upper bound on the processing time. Albers and Eckl recently studied the multiprocessor scheduling with testing; among others, for the non-preemptive setting they presented an approximation algorithm with competitive ratio approaching 3.1016 when the number of machines tends to infinity and an improved approximation algorithm with competitive ratio approaching 3 when all test operations take one unit of time each. We propose to first sort the jobs into non-increasing order of the minimum value between the upper bound and the testing time, then partition the jobs into three groups and process them group by group according to the sorted job order. We show that our algorithm achieves better competitive ratios, which approach 2.9513 when the number of machines tends to infinity in the general case; when all test operations each takes one time unit, our algorithm achieves even better competitive ratios approaching 2.8081.

     

Modeling of Distributed Generators Resilience Considering Lifeline Dependencies During Extreme Events

This article derives distributed generators resilience models considering lifeline dependencies during extreme events. The effects on power resilience of storage capacity, fuel delays, and fuel order placements are analyzed. Results indicate that storage capacity has an important role in improving overall power supply resilience as seen by loads. In addition, the presented models provide a quantifiable approach in evaluating fuel delivery resilience. The models facilitate studying fuel scheduling policies and local fuel storage sizing for specified resilience requirements. It is observed that tank autonomy greatly affects the flexibility in employing scheduling policies supplying fuel to generators. Resilience dependence on buffer autonomy is high during the first few days of extreme events, and this could have considerable effects on managing evacuations and rescue operations.