原材料价格波动下的库存与生产联合决策

价格波动的情况下如何进行原材料采购,并在产品的生产决策中如何权衡市场需求、产品价格以及采购与库存成本等问题是当前很多企业面临的普遍难题.对此类问题,假定原材料的价格波动服从马尔可夫过程,成品的市场需求为与价格相关的随机变量,进而建立了多周期库存采购与生产联合决策模型,并分析了系统的动态最优策略.模型同时考虑了原材料买进或者卖出决策和成品生产决策.研究结果表明,模型的最优策略,即原材料库存决策与成品生产决策均满足动态基库存策略.同时证明了一系列性质,这些性质展示了原材料价格波动下最优库存策略的特征.数值实验进一步验证了模型的最优策略,并研究了参数变化时最优策略的变化.     

Changing risk preferences in supply chain inventory decisions

The risk preferences of managers may cause their inventory ordering decisions to deviate from the optimal policy. Past studies in operations management have produced mixed results. This study examines this proposition using decision data collected from a supply chain experiment. This article finds that changing the risk preferences of managers with respect to demand changes and supplier failures is a significant behavioural factor in explaining deviations in ordering decisions. This result provides an additional behavioural cause in explaining the bullwhip effect in supply chains. It also provides insights on the challenges for reducing the bullwhip effect in supply chains.     

Ability, individual development and optimal selection decisions

The paper analyzes different selection policies in education and business. We show that incorrect self-perceptions combined with imperfect performance measurement may cause significant welfare losses in selective educational systems, in particular if selection starts too early. Of course, these welfare losses can be mitigated by an investment in better ability assessment. However, an affirmative action policy could serve the same purpose as such an investment. We apply our analysis also to diversity management in firms. Based on positive discrimination we establish an efficiency argument for diversity management.     

Estimating the optimal order quantity and the maximum expected profit for single-period inventory decisions

The paper considers the classical single-period inventory model, also known as the Newsboy Problem, with the demand normally distributed and fully observed in successive inventory cycles. The extent of applicability of such a model to inventory management depends upon demand estimation. Appropriate estimators for the optimal order quantity and the maximum expected profit are developed. The statistical properties of the two estimators are explored for both small and large samples, analytically and through Monte-Carlo simulations. For small samples, both estimators are biased. The form of distribution of the optimal order quantity estimator depends upon the critical fractile, while the distribution of the maximum expected profit estimator is always left-skewed. Small samples properties of the estimators indicate that, when the critical fractile is set over a half, the optimal order quantity is underestimated and the maximum expected profit is overestimated with probability over 50%, whereas the probability of overestimating both quantities exceeds again 50% when the critical fractile is below a half. For large samples, based on the asymptotic properties of the two estimators, confidence intervals are derived for the corresponding true population values. The validity of confidence intervals using small samples is tested by developing appropriate Monte-Carlo simulations. In small samples, these intervals attain acceptable confidence levels, but with high unit shortage cost, for the case of maximum expected profit, significant reductions in their precision and stability are observed.     

Joint pricing and ordering policy for a deteriorating inventory with partial backlogging

In this paper, a deterministic inventory model for deteriorating items with time-dependent backlogging rate is developed. The demand and deterioration rate are known, continuous, and differentiable function of price and time, respectively. Under these general assumptions, we first prove that the optimal replenishment schedule not only exists but is unique, for any given selling price. Next, we show that the total profit is a concave function of price when the replenishment schedule is given. We then provide a simple algorithm to find the optimal selling price and replenishment schedule for the proposed model. Finally, we use a numerical example to illustrate the algorithm.     

An integrated supplier selection and inventory problem with multi-sourcing and lateral transshipments

In this research, we consider the supplier selection problem of a firm offering a single product via multiple warehouses. The warehouses face stationary, stochastic demand and replenish their inventory via multiple suppliers, to be determined from a set of candidates, with varying price, capacity, quality, and disruption characteristics. Additionally, the warehouses may simultaneously replenish their inventory from other warehouses proactively. With these characteristics, the problem is a multi-sourcing, supplier selection, and inventory problem with lateral transshipments. Even though the benefits of multi-sourcing and lateral transshipments have been presented in the literature individually to mitigate risks associated with uncertain demand and disrupted supply, the intertwined sourcing and inventory decisions under these settings have not been investigated from a quantitative perspective. We develop a decomposition based heuristic algorithm, powered with simulation. While the decomposition based heuristic determines a solution with supplier selection and inventory decisions, the simulation model evaluates the objective function value corresponding to each generated solution. Experimental results show, contrary to the existing literature, inferior decisions may result when considering the selection of suppliers solely on unit and/or contractual costs. We also evaluate the impact of multi-sourcing with rare but long disruptions compared to frequent but short ones.     

单产品物流网络系统的联合决策模型

考虑全球制造环境下单产品在多个供应商和多个用户之间的联合物流决策问题,包括供应商指定的生产任务、生产批量、供应商和用户之间的年运输量和订货批量.联合决策过程可以看作是两层决策,其中第一层是供应商指定的生产任务和生产批量的联合决策(APLS),第二层是运输和订货批量的联合决策(TOQ).因此,提出了基于两层分解的启发式算法来求解这样的联合决策模型(JDM).结合实际例子对模型和算法进行了仿真分析,结果证明了基于两层分解的启发式算法的有效性.     

Joint product assortment,inventory and price optimization to attract loyal and non-loyal customers

In this paper, we analyze the emerging retail practice of carrying a combined product assortment consisting of both regular “standard” products and more fashionable and short-lived “special” products. The purpose of this practice is to increase store traffic by attracting heterogeneous classes of customers, which drives up sales of standard products due to the potential cross-selling effect. Customers who are primarily attracted by special products will also buy some standard products. In this context, we analyze three decisions that are crucial for a retailer׳s commercial success: the product assortment, the inventory levels and the pricing. We propose an optimization model and an iterative heuristic to analyze the trade-offs between the combined product assortment, the inventory level and the price per product when there is limited shelf space. Using numerical experiments, we show that our heuristic can be trusted and that its accuracy improves when the number of products increases. Our findings indicate that to attract more customers for standard products, a retailer may benefit from carrying low priced special products which, if considered in isolation, would be non-profitable. As the cross-selling effect decreases, a retailer should focus more on the standard assortment by increasing its size and decreasing the prices. However, introducing special products and ignoring the cross-selling effect may decrease a retailer׳s profitability. We show that the introduction of special products involves more than just choosing the right specials for non-loyal customers but impacts the global assortment planning, the standard products and the products pricing.     

Using real-time simulations to make medical technology decisions

Study how one health care organization evaluated various vendors of evidence-based content for making clinical decisions.     

基于σ/ Q 的库存控制中安全库存的优选策略

研究了单项目库存控制问题中的安全库存选择策略,评论了安全库存的决定要素,讨论了基于以上要素的成本构成.进一步讨论了安全库存策略在理论和实践应用中的矛盾,提出了一种实践中容易操作的安全库存的直观求解方法,以利于管理者实际运用,有效克服运作环境的不确定性.     

Free or bundled: Channel selection decisions under different power structures

The smart phone industry has unique supply chain relationships. Companies at all levels of the supply chain compete and coordinate with each other for market share and profit. This paper examines the impact of power structures on the decision of pricing and channel selection between a free channel and a bundled channel. We investigate the smart phone supply chain that consists of a handset manufacturer and a telecom service operator. Based on game theory models, the manufacturer׳s optimal retail pricing policies in free and bundled channels and the telecom service operator׳s optimal subsidy policies in a bundled channel are derived under different power structures. It is demonstrated that the firm that has higher channel power will gain more profit, and the smart phone supply chain׳s profit in a Vertical Nash (VN) power structure is higher than that in Telecom Service Operator-Stackelberg (TS) and Manufacturer-Stackelberg (MS) power structures. It is also shown that the smart phone supply chain will choose a bundled channel in TS and MS power structures under certain conditions and will select a free channel in a VN power structure.     

Joint modified block replacement and production/inventory control policy for a failure-prone manufacturing cell

This paper considers a joint preventive maintenance (PM) and production/inventory control policy of an unreliable single machine, mono-product manufacturing cell with stochastic non-negligible corrective and preventive delays. The production/inventory control policy, which is based on the hedging point policy (HPP), consists in building and maintaining a safety stock of finished products in order to respond to demand and to avoid shortages during maintenance actions. Without considering the impact of preventive and corrective actions on the overall performance of the production system, most authors working in the reliability and maintainability domains confirm that the age-based preventive maintenance policy (ARP) outperforms the classical block-replacement policy (BRP). In order to reduce wastage incurred by the classical BRP, we consider a modified block replacement policy (MBRP), which consists in canceling a preventive maintenance action if the time elapsed since the last maintenance action exceeds a specified time threshold. The main objective of this paper is to determine the joint optimal policy that minimizes the overall cost, which is composed of corrective and preventive maintenance costs as well as inventory holding and backlog costs. A simulation model mimicking the dynamic and stochastic behavior of the manufacturing cell, based on more realistic considerations of the real behavior of industrial manufacturing cells, is proposed. Based on simulation results, the joint optimal MBRP/HPP parameters are obtained through a numerical approach that combines design of experiment, analysis of variance and response surface methodologies. The joint optimal MBRP/HPP policy is compared to classical joint ARP/HPP and BRP/HPP optimal policies, and the results show that the proposed MBRP/HPP outperforms the latter. Sensitivity analyses are also carried out in order to confirm the superiority of the proposed MBRP/HPP, and it is observed that for practitioners, the proposed joint MBRP/HPP offers not only cost savings, but is also easy to manage, as compared to the ARP/HPP policy.     

The effect of preservation technology investment on a non-instantaneous deteriorating inventory model

Considering an inventory system with a non-instantaneous deteriorating item, our objective is to study the effect of preservation technology investment on inventory decisions. The generalized productivity of invested capital, deterioration and time-depend partial backlogging rates are used to model the inventory system. The basic results of fractional programming are employed to prove the uniqueness of the global maximum for each case. We also establish several structural properties on finding the optimal replenishment and preservation technology strategies. Further, we use a couple of numerical examples to illustrate the results and conclude the paper with suggestions for possible future researches.     

Mean-risk analysis of radio frequency identification technology in supply chain with inventory misplacement: Risk-sharing and coordination

This paper investigates the application of radio frequency identification (RFID) technology to eliminate the misplacement problems in the supply chain, which consists of a risk-neutral manufacturer and a risk-averse retailer. By considering both fixed cost and tag cost of RFID implementation, we study the agents' incentives to adopt RFID in both uncoordinated and coordinated cases. We focus on analyzing the impact of risk attitudes on the agents’ incentives and on the supply chain coordination. The central semi-deviation is adopted to measure the retailer's risk attitude. In the uncoordinated case, we find that, in order to induce the retailer to adopt RFID, the manufacturer must assume more fixed cost if the retailer is more risk-averse. In the coordinated case, we first show that the standard revenue sharing contract does not always coordinate the channel. If the channel is coordinated, we observe that the agents’ incentives will be perfectly aligned and independent of the risk attitudes, if the revenue sharing ratio equals the fixed cost sharing ratio. Then we propose a risk-sharing contract that offers the risk protection to the retailer, to achieve the channel coordination. An interesting finding is that the manufacturer's incentive will not decrease with the tag cost, if she takes much risk from the retailer. The corresponding impacts of RFID adoption on the two contracts are also analyzed in this paper. Finally, a case study in a tobacco industry is presented to show the real RFID cost in practice.     

Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing

This paper presents a stochastic mixed integer programming approach to integrated supplier selection and customer order scheduling in the presence of supply chain disruption risks, for a single or dual sourcing strategy. The suppliers are assumed to be located in two different geographical regions: in the producer's region (domestic suppliers) and outside the producer's region (foreign suppliers). The supplies are subject to independent random local disruptions that are uniquely associated with a particular supplier and to random semi-global (regional) disruptions that may result in disruption of all suppliers in the same geographical region simultaneously. The domestic suppliers are relatively reliable but more expensive, while the foreign suppliers offer competitive prices, however material flows from these suppliers are more exposed to unexpected disruptions. Given a set of customer orders for products, the decision maker needs to decide which single supplier or which two different suppliers, one from each region, to select for purchasing parts required to complete the customer orders and how to schedule the orders over the planning horizon, to mitigate the impact of disruption risks. The problem objective is either to minimize total cost or to maximize customer service level. The obtained combinatorial stochastic optimization problem will be formulated as a mixed integer program with conditional value-at-risk as a risk measure. The risk-neutral and risk-averse solutions that optimize, respectively average and worst-case performance of a supply chain are compared for a single and dual sourcing strategy and for the two different objective functions. Numerical examples and computational results are presented and some managerial insights on the choice between the two sourcing strategies are reported.     

基于聚类挖掘的供应链绩效评价的标杆选择法

标杆法作为供应链绩效评价的一种方法具有重要的应用价值,而如何针对既定目标选 择合适的标杆并提供可信的依据是这类方法的瓶颈. 针对这个问题,提出利用基于密度的聚类 挖掘技术采集分析供应链的特征,为使用标杆法比较和改善供应链的绩效提供决策依据. 首先 对已知供应链的绩效指标值数据进行标准化处理,然后采用基于密度的聚类挖掘技术(改进的 K - 均值聚类方法) 进行分类,通过分析各类供应链的特点和差异解决了标杆选择的问题,最 后设计了一个算例说明方法的应用.     

Materials receiving capacity and inventory management

This paper analyses the optimal level of materials receiving capacity for a manufacturer that receives deliveries from many suppliers. Inventory levels and inventory carrying costs depend on the frequency of deliveries and thus, on the materials receiving capacity. An analytic model that captures the tradeoff between inventory costs and materials receiving costs is presented and discussed. The receiving cost is modeled as increasing in discrete jumps of varying sizes whenever materials receiving resources are added. Practical issues in implementing the model are highlighted and methods to reduce the marginal materials receiving cost are discussed. The paper also discusses connections to the JIT approach for production environments where materials receiving is heavily automated.     

Optimal inventory cycle counting

The heart of inventory transactions management involves obtaining an accurate count of on-hand inventories employing different procedures. Among such procedures cycle counting is said to provide better inventory record accuracy for financial control and production planning. However, these procedures use rather arbitrary basis for classifying items and for setting the count frequency within each strata. This paper develops a simple optimization model of inventory cycle counting based on traditional stratified sampling theory. Such a model allows the inventory manager to make statistically supported statements regarding inventory record accuracy so as to meet financial control requirements with a minimum of cycle counting effort. A numerical example is included to illustrate the model.     

世界音乐界的不解之缘——瑞士豪利时（Oris）的音乐之旅

总部位于瑞士,创始于1904年的瑞士名表豪利时（Oris）,就是坚持以传统的瑞士工艺创制成真正完美的机械腕表的典范。近百年来对手表品质及内涵的不断追求和完善,使豪利时品牌获得了人们广泛的尊崇。其四大系列之一的文化艺术系列,一直是世界音乐界的良好合作伙伴。