Coping with shortages caused by disruptive events in automobile supply chains

Unpredictable disruptive events significantly increase the difficulty of the management of automobile supply chains. In this paper, we propose an automobile production planning problem with component chips substitution in a finite planning horizon. The shortage of one chip can be compensated by another chip of the same type with a higher-end feature at an additional cost. Therefore, the automobile manufacturer can divert the on-hand inventory of chips to product lines that are more profitable in the event of shortages caused by supply chain disruptions. To cope with this, we propose a max-min robust optimization model that captures the uncertain supplies of chips. We show that the robust model has a mixed-integer programming equivalence that can be solved by a commercial IP solver directly. We compare the max-min robust model with the corresponding deterministic and two-stage stochastic models for the same problem through extensive numerical experiments. The computational results show that the max-min robust model outperforms the other two models in terms of the average and worst-case profits.     

Selling to strategic and loss‐averse consumers: Stocking,procurement, and product design policies

Motivated by the presence of loss‐averse decision making behavior in practice, this article considers a supply chain consisting of a firm and strategic consumers who possess an S‐shaped loss‐averse utility function. In the model, consumers decide the purchase timing and the firm chooses the inventory level. We find that the loss‐averse consumers' strategic purchasing behavior is determined by their perceived gain and loss from strategic purchase delay, and the given rationing risk. Thus, the firm that is cognizant of this property tailors its inventory stocking policy based on the consumers' loss‐averse behavior such as their perceived values of gain and loss, and their sensitivity to them. We also demonstrate that the firm's equilibrium inventory stocking policy reflects both the economic logic of the traditional newsvendor inventory model, and the loss‐averse behavior of consumers. The equilibrium order quantity is significantly different from those derived from models that assume that the consumers are risk neutral and homogeneous in their valuations. We show that the firm that ignores strategic consumer's loss‐aversion behavior tends to keep an unnecessarily high inventory level that leads to excessive leftovers. Our numerical experiments further reveal that in some extreme cases the firm that ignores strategic consumer's loss‐aversion behavior generates almost 92% more leftovers than the firm that possesses consumers’ loss‐aversion information and takes it into account when making managerial decisions. To mitigate the consumer's forward‐looking behavior, we propose the adoption of the practice of agile supply chain management, which possesses the following attributes: (i) procuring inventory after observing real‐time demand information, (ii) enhanced design (which maintains the current production mix but improves the product performance to a higher level), and (iii) customized design (which maintains the current performance level but increases the variety of the current production line to meet consumers’ specific demands). We show that such a practice can induce the consumer to make early purchases by increasing their rationing risk, increasing the product value, or diversifying the product line. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 435–453, 2015     

Sojourn times in a two‐stage queueing network with blocking

The model considered in this paper involves a tandem queue consisting of a sequence of two waiting lines. The main feature of our model is blocking, i.e., as soon as the second waiting line reaches a certain upper limit, the first line is blocked. The input of units to the tandem queue is the MAP (Markovian arrival process), and service requirements are of phase type. Our objective is to study the sojourn time distribution under the first‐come‐first‐serve discipline by analyzing the sojourn time through times until absorption in appropriately defined quasi‐birth‐and‐death processes and continuous‐time Markov chains. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

基于场的装备物资供应保障适应性配置决策

根据与物理场的相似性,将装备物资供应保障抽象为供应保障场,在定义场强度的基础上,提出基于场强度的反演运算进行供应保障资源配置的方法,给出了通过实时获取战场信息跟踪供应保障场的变化进行保障资源适应性配置决策的流程。     

通用军械装备维修备件合同商保障方式研究

提出了备件合同商保障的概念,给出了备件合同商保障内容和维度,分析了备件合同商保障的特征,着重从备件的存储方式和供应方式两个方面进行了定性分析,为实施备件合同商保障奠定了理论基础．     

消防气压给水设备应用探讨

通过对消防气压给水设备在消防给水系统中的作用分析,讨论了消防气压给水设备＂大罐＂和＂小罐＂的区别,指出了不同作用时气压罐消防水容积和稳压泵流量的要求,并提出了气压给水设备设计应着重把关的问题,同时阐明了该设备运行时的气压控制、水流控制及稳压泵供电等要求。     

气溶胶灭火装置在工业供电系统中的应用

分析工业供电系统的火灾特点和原因 ,结合部分工程实例和气溶胶灭火装置的特性 ,提出该类产品在工业供电系统应用中的优势和施工中的注意事项 ,并展望其应用前景     

The impact of manufacturer rebates on supply chain profits

Manufacturer rebates are commonly used as price discount tools for attracting end customers. In this study, we consider a two‐stage supply chain with a manufacturer and a retailer, where a single seasonal product faces uncertain and price‐sensitive demand. We characterize the impact of a manufacturer rebate on the expected profits of both the manufacturer and the retailer. We show that unless all of the customers claim the rebate, the rebate always benefits the manufacturer. Our results thus imply that “mail‐in rebates,” where some customers end up not claiming the rebate, particularly when the size of the rebate is relatively small, always benefit the manufacturer. On the other hand, an “instant rebate,” such as the one offered in the automotive industry where every customer redeems the rebate on the spot when he/she purchases a car, does not necessarily benefit the manufacturer. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

Machine scheduling with an availability constraint and job delivery coordination

In this paper we study the scheduling problem that considers both production and job delivery at the same time with machine availability considerations. Only one vehicle is available to deliver jobs in a fixed transportation time to a distribution center. The vehicle can load at most K jobs as a delivery batch in one shipment due to the vehicle capacity constraint. The objective is to minimize the arrival time of the last delivery batch to the distribution center. Since machines may not always be available over the production period in real life due to preventive maintenance, we incorporate machine availability into the models. Three scenarios of the problem are studied. For the problem in which the jobs are processed on a single machine and the jobs interrupted by the unavailable machine interval are resumable, we provide a polynomial algorithm to solve the problem optimally. For the problem in which the jobs are processed on a single machine and the interrupted jobs are nonresumable, we first show that the problem is NP‐hard. We then propose a heuristic with a worst‐case error bound of 1/2 and show that the bound is tight. For the problem in which the jobs are processed on either one of two parallel machines, where only one machine has an unavailable interval and the interrupted jobs are resumable, we propose a heuristic with a worst‐case error bound of 2/3. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

A supply chain design model with unreliable supply

Uncertainties abound within a supply chain and have big impacts on its performance. We propose an integrated model for a three‐tiered supply chain network with one supplier, one or more facilities and retailers. This model takes into consideration the unreliable aspects of a supply chain. The properties of the optimal solution to the model are analyzed to reveal the impacts of supply uncertainty on supply chain design decisions. We also propose a general solution algorithm for this model. Computational experience is presented and discussed. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007