Reliable Supply Chain Network Design

Risk management in supply chains has been receiving increased attention in the past few years. In this article, we present formulations for the strategic supply chain network design problem with dual objectives, which usually conflict with each other: minimizing cost and maximizing reliability. Quantifying the total reliability of a network design is not as straightforward as total cost calculation. We use reliability indices and develop analytical formulations that model the impact of upstream supply chain on individual entities’ reliability to quantify the total reliability of a network. The resulting multiobjective nonlinear model is solved using a novel hybrid algorithm that utilizes a genetic algorithm for network design and linear programming for network flow optimization. We demonstrate the application of our approach through illustrative examples in establishing tradeoffs between cost and reliability in network design and present managerial implications.     

基于顾客需求偏好的面向无人零售终端的供应链资源整合优化研究

面向新零售的无人零售终端所关注的焦点是如何为顾客提供满意的购物体验。目前,无人零售终端在提供服务时较多关注不同场景下顾客对商品类型的需求,而往往忽略价格、品质和终端操作便捷性等其他差异化的需求。而无人零售的无人值守、需要灵活补货和配货等特点,决定了其在提供差异化服务时,离不开供应链网络的有效支撑,这就需要对供应链网络中的各类资源进行合理整合。本文在分析不同场景下顾客需求偏好的基础上,重点探讨了面向无人零售终端资源整合中的供应链成员筛选机理,有针对性地提出了关键因素的挖掘和分类方法。在此基础上,构建了对应的整合优化模型和求解算法,并通过算例验证了方法和算法的可行性、有效性与可操作性。     

具有遗憾值约束的鲁棒供应链网络设计模型研究

考虑不确定性环境,研究战略层次的供应链网络鲁棒设计问题,目标是设计参数发生摄动时,供应链性能能够保持稳健性。基于鲁棒解的定义,建立从上游供应商选择到下游设施选址-需求分配的供应链网络设计鲁棒优化模型;提出确定遗憾值限定系数上限和下限的方法,允许决策者调节鲁棒水平,选择多种供应链网络结构;通过模型分解与协调,设计了供应链节点配置的禁忌搜索算法。算例的计算结果表明了禁忌搜索算法具有良好的收敛特性,以及在处理大规模问题上的优越性;同时也反映了利用鲁棒优化模型进行供应链网络设计,可以有效规避投资风险。     

基于双层规划的供应链二级分销网络优化设计模型

从供应链集成的角度出发,利用双层规划模型描述了二级分销网络优化问题,充分考虑了网络决策部门及客户双方的自身及共同利益。同时设计了启发式求解算法,最后用一简单实例验证了模型及其算法的有效性。     

An inventory control policy for liquefied natural gas as a transportation fuel

In this paper, we study a novel stochastic inventory management problem that arises in storage and refueling facilities for Liquefied Natural Gas (LNG) as a transportation fuel. In this inventory problem, the physio-chemical properties of LNG play a key role in the design of inventory policies. These properties are: (1) LNG suffers from both quantity decay and quality deterioration and (2) the quality of on-hand LNG can be upgraded by mixing it with higher-quality LNG. Given that LNG quality can be upgraded, an inventory control policy for this problem needs to consider the removal of LNG as a decision variable. We model and solve the problem by means of a Markov Decision Process (MDP) and study the structural characteristics of the optimal policy. The insights obtained in the analysis of the optimal policy are translated into a simple, though effective, inventory control policy in which actions (i.e., replenishment and/or removal) are driven by both the quality and the quantity of the inventories. We assess the performance of our policy by means of a numerical study and show that it performs close to optimal in many numerical instances. The main conclusion of our study is that it is important to take quality into consideration when design inventory control policies for LNG, and that the most effective way to cope with quality issues in an LNG inventory system involves both the removal and the replenishment of inventories.     

供应中断风险下OEM供应链弹性运作与提升策略

供应中断是OEM供应链中企业面临的主要风险。本文基于供应链弹性分析的角度，将OEM供应链弹性运作问题描述为多变量耦合控制模型，构建了可变结构的弹性控制系统，研究了在供应中断风险冲击下OEM供应链弹性交互影响机制。在此基础上，提出了一种有针对性的提升供应链弹性的深度学习机制，此算法比传统的BP神经网络更加能够提高供应链绩效，并结合案例进行验证。研究结果表明：当供应中断发生时，深度学习算法可有效提升OEM供应链弹性，最大程度减轻企业损失。     

供应链分销系统双层优化模型

分销渠道决策在整个供应链管理中非常关键,因为它直接影响着其它的市场决策. 从供 应链集成的角度出发,利用双层规划模型描述了二级分销网络优化问题,充分考虑了网络决策 部门及客户双方的自身及共同利益. 同时设计了启发式求解算法,最后用简单算例验证了模型 及其算法的有效性.     

Bounds of Relative Regret Limit in p‐Robust Supply Chain Network Design

This research studies the p‐robust supply chain network design with uncertain demand and cost scenarios. The optimal design integrates the supplier selection together with the facility location and capacity problem. We provide a new framework to obtain the relative regret limit, which is critical in the robust supply chain design but is assumed to be a known value in the existing literature. We obtain lower and upper bounds for relative regret limit and obtain a sequence of optimal solutions for series relative regret limits between the upper and lower bounds. An algorithm for p‐robust supply chain network design is provided. A series of numerical examples are designed to find the properties of the bottleneck scenarios. A scenario with low probability and a low optimal objective function value for the scenario has a greater chance of being a bottleneck. To focus only on the influence from the relative regret, we also introduce three separate new objective functions in p‐robust design. The proposed new theories and approaches provide a sequence of options for decision makers to reduce the marketing risks effectively in supply chain network design.     

Cross dock scheduling: Classification,literature review and research agenda

At cross docking terminals incoming deliveries of inbound trucks are unloaded, sorted, moved across the dock and finally loaded onto outbound trucks, which immediately leave the terminal towards their next destination in the distribution chain. Accordingly, a cross dock is a consolidation point in a distribution network, where multiple smaller shipments can be merged to full truck loads in order to realize economies in transportation. In this context, the truck scheduling problem, which decides on the succession of truck processing at the dock doors, is especially important to ensure a rapid turnover and on-time deliveries. Due to its high real-world significance, several truck scheduling procedures have been introduced during recent years, which all treat specific cross dock settings. In order to structure and promote scientific progress, this paper introduces a classification of deterministic truck scheduling. With the help of this classification, existing literature is reviewed and future research needs are identified. Moreover, we represent a yet unexplored class of truck scheduling problems which is highly relevant in real-world distribution networks.     

考虑技术投资的供应链网络下可交易污染排放许可均衡问题

构建了包含多污染物、多污染接收点的供应链网络,考虑了生产技术和减排技术投资,对可交易的污染排放许可下的供应链网络进行了均衡分析,给出了变分不等式框架,建立了均衡模型。模型明确地处理了空间差异,同时保证了通过初始污染排放许可分配就可达到指定的环境标准。提出了模型的求解算法,最后利用提出的模型及算法对算例进行了计算,得到利润最大化下供应链网络中各工厂的产品生产量、排放量、污染排放许可的均衡分配额和污染排放许可的交易价格、技术最优投资额,并分析了成本函数参数以及工厂数量的变化对生产技术投资和减排技术投资的影响。     

Modeling a low-carbon garment supply chain

This article attempts to introduce indirect carbon emission and trade-credit concept in a network optimisation model for sustainable supply chain. The proposed model optimises total cost, total direct carbon emission, total indirect emission in the form of embodied carbon footprint of the raw material and total trade-credit amount over the purchased item in a supply chain. The model calculates the total cost by considering purchasing cost, logistics cost, handling cost and manufacturing cost. It attempts to measure the direct emission involved in manufacturing and logistics operations. The model has the capability to consider dissimilar trucks used for transportation according to their operating cost and carbon emission. Multi-objective goal programming is applied to deal with four objectives to find a tradeoff among these objectives. The result suggests that managers should capture the direct as well as the indirect emission which helps in arriving at appropriate strategy for a sustainable supply chain. The effectiveness of the proposed model is demonstrated through a case of a garment supply chain. This model also supports in deciding appropriate goal for carbon emission, supply chain costs, etc.     

Planning of a decentralized distribution network using bilevel optimization

This paper proposes a bilevel optimization problem to model the planning of a distribution network that allows us to take into account how decisions made at the distribution stage of the supply chain can affect and be affected by decisions made at the manufacturing stage. Usually, the distribution network design problem decides on the opening of depots and the distribution from the depots to customers only and pays no attention to the manufacturing process itself. By way of example, the paper discusses the implications of formulating a bilevel model to integrate distribution and manufacturing, maintaining the hierarchy existing in the decision process. The resulting model is a bilevel mixed integer optimization problem. Hence, only small instances can be optimally solved in an acceptable computing time. In order to be able to solve the optimization model for realistic large systems, a metaheuristic approach based on evolutionary algorithms is developed. The algorithm combines the use of an evolutionary algorithm to control the supply of depots with optimization techniques to determine the delivery from depots to customers and the supply from manufacturing plants to depots. A computational experiment is carried out to assess the efficiency and robustness of the algorithm.     

A multi-stage stochastic supply network design problem with financial decisions and risk management

In this paper, a multi-period supply chain network design problem is addressed. Several aspects of practical relevance are considered such as those related with the financial decisions that must be accounted for by a company managing a supply chain. The decisions to be made comprise the location of the facilities, the flow of commodities and the investments to make in alternative activities to those directly related with the supply chain design. Uncertainty is assumed for demand and interest rates, which is described by a set of scenarios. Therefore, for the entire planning horizon, a tree of scenarios is built. A target is set for the return on investment and the risk of falling below it is measured and accounted for. The service level is also measured and included in the objective function. The problem is formulated as a multi-stage stochastic mixed-integer linear programming problem. The goal is to maximize the total financial benefit. An alternative formulation which is based upon the paths in the scenario tree is also proposed. A methodology for measuring the value of the stochastic solution in this problem is discussed. Computational tests using randomly generated data are presented showing that the stochastic approach is worth considering in these types of problems.     

Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty

The design and planning of resilient supply chains is a major challenge due to the increasing complexity of these systems that operate in a global market and therefore are more exposed to disruptions. In the present work a design and planning model that integrates demand uncertainty is applied to five supply chain structures that are submitted to different types of disruptions. Disruptions are modelled in a probabilistic manner, resulting in the incorporation of two sources of uncertainty. Eleven indicators are considered to assess the supply chains’ resilience, which comprise network design, centralization and operational indicators. The goal is to provide managers what are expected operational impacts (measured by the operational indicators) by assessing the behavior of network and centralization indicators and their known resilience behaviors from the literature. A case study of a European supply chain is used to illustrate the methodology and a discussion on the results obtained is presented in order to conclude which main characteristics a manager should consider when designing and planning resilient supply chains.     

考虑服务流的产品服务供应链网络均衡模型

产品服务供应链在向客户制造高质量产品的同时，也提供了产品全生命周期的专业服务，服务的嵌入增加了供应链协调的复杂性。考虑产品服务的双重需求，在分析各主体的运作行为的基础上，构建了包括多个制造商和多个销售商的多主体供应链网络；运用变分不等式刻画了制造商层、销售服务集成商层和需求市场的最优运作行为及其达成均衡的条件；最后，通过修正投影算法对数值算例进行了仿真。研究结果表明：产品服务供应链网络中的产品与服务均衡流相互影响，其中，服务水平直接影响到了产品需求；降低产品的售价将有利于服务价格和效益的提升。研究结论进一步印证了在产品服务供应链网络中承载于产品的服务将逐渐成为价值创造的主体。     

多级供应链系统成本分析随机网络模型及算法研究

供应链成本管理是企业战略管理的核心组成部分。为研究多级供应链网络系统的成本组成及其分布特征、分析各节点企业的成本管理对多级供应链网络系统的影响、找到供应链系统成本管理中的薄弱环节和关键企业,本文构建了多级供应链系统成本的随机网络分析模型。首先研究了模型的结构性质特征,给出成本分布特征的解析算法。然后扩展模型,分别从系统成本类型构成(生产成本、库存成本和物流成本)和系统对企业成本波动的灵敏度两个角度深入研究多级供应链网络成本问题。数值算例分析结果说明了多级供应链网络系统成本分析模型和相关算法的有效性和实用性。     

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。     

非平稳需求下考虑碳配额的供应链选址-库存模型与算法研究

针对非平稳需求下考虑碳配额的多期、多需求情景的三级供应链选址-库存问题，构建了库存策略（t，s，S）下供应链运营期望收益最大化的两阶段选址-库存随机优化模型，依据供应链企业不同着眼点下的决策流程，提出了一种三步骤的分层级启发式算法，该算法包含了选址导向和需求导向的两种子问题序贯求解模式。数值算例验证了在不同问题规模及需求类型下算法求解的有效性，同时分析了供应链网络设计、各成本占比和运营收益对不同供应链成本结构、需求不确定性与碳配额的敏感性，并给出了管理上的启示。     

考虑交易安全风险控制投入的在线旅游供应链网络均衡模型

基于包括供应商、平台和消费市场的三层供应链网络结构，利用变分不等式刻画均衡态时在线旅游供应链网络各成员的最优经济行为，以及平台交易安全风险控制投入对供应链平台企业、供应链整体的风险水平和期望收益的影响。研究发现，在平台企业风险控制投入相同情况下，平台和消费市场的产品交易数量和价格大致相同，验证了模型的合理性和有效性。其次，随着交易安全风险控制投入的增加，平台自身交易安全风险下降，供应链网络整体的交易安全水平和交易数量上升，但平台自身的期望收益下降。最后，随着更多的平台加入，平台的期望收益下降，市场需求价格下降，消费者获利。但部分平台企业的搭便车行为，会导致供应链整体的交易安全风险水平上升。     

众包供应链基于On/OffLine混合定制设计生产决策模型分析

互联网平台经济（Platform Economy）正颠覆传统企业商业模式，众包供应链（Crowdsourcing Supply Chain，CSC）作为一种新型的"互联网平台+设计创新"供应链，也正成为人们关注和研究的热点。本文在订单定制设计模式（Engineering to Order，ETO）的基础上，将定制设计和订单生产两环节相结合，并以交货期为驱动，按常规生产时间和加班生产时间来优化生产流程。在此框架下，建立了线下（Offline）自行定制设计的供应链生产模型；接着结合互联网众包平台的特点，以及众包线上（Online）和线下（Offline）的互补性，将众包线上定制设计环节有机嵌入融合到线下自行定制设计供应链中，以此优化和构建出基于众包的线上线下混合定制设计的供应链生产决策模型，设计出众包线上定制设计和线下定制设计动态切换条件；并通过粒子群算法（Particle Swarm Optimization，PSO）对上述模型进行求解；最后通过实例进行分析，发现定制订单数量不多时，线上线下混合定制设计对成本的降低不是很显著，但随着订单数量越多，线上线下混合定制设计优势将显著变化，并且具有一定程度的抗风险性；通过这个转换点也发现，众包定制设计的订单生产最好安排在期初和期末，众包线上定制设计订单应尽可能减少挤占线下自行设计的常规生产时间，而应转向在加班时间生产更为经济；同时，通过增加对众包设计者的设计报酬，发现不仅对整个供应链的成本影响不大，反而对众包设计者形成较大激励作用，进一步证明该模式的可行性和实用性。