云计算中基于TPM的多银行电子现金系统

针对云计算的虚拟化技术可以解决传统网络中电子现金系统存在的隐私泄露、交易不规范和高成本投入问题, 在已有的工作中, 考虑商家和用户使用同一银行在一定程度上限制了电子现金广泛使用的情况, 提出了一种基于TPM(trusted platform module)的可信云平台多银行电子现金方案。该方案从电子现金支付的效率和安全性方面考虑, 利用群签名和椭圆曲线算法ECC提高协议的执行效率, 运用可信平台模块提供的隐私保护和远程证明功能加强支付协议的安全性。最后, 对方案的安全性和效率进行分析。     

Joint determination of order quantity and reorder point of continuous review model under quantity and freight rate discounts

The increased emphasis on transportation costs has enhanced the need to develop models with transportation consideration explicitly. However, in stochastic inventory models, the transportation cost is considered implicitly as part of fixed ordering cost and thus is assumed to be independent of the size of the shipment. As such, the effect of the transportation and purchasing costs are not adequately reflected in final planning decisions. In this paper, transportation and purchasing considerations are integrated with continuous review inventory model. The objective is to view the system as an integrated whole and determine the lot size and reorder point which minimize the expected total cost per unit time. In addition, procedures are developed to solve the proposed models. Numerical experiments are also performed to explore the effect of key parameters on lot size, reorder point and expected total cost. The new models have a significant impact on lot size, reorder point and expected total cost. Savings up to 17.15% of the expected total cost are realized when using the proposed models.     

The inventory-routing problem with transshipment

This paper introduces the Inventory-Routing Problem with Transshipment (IRPT). This problem arises when vehicle routing and inventory decisions must be made simultaneously, which is typically the case in vendor-managed inventory systems. Heuristics and exact algorithms have already been proposed for the Inventory-Routing Problem (IRP), but these algorithms ignore the possibility of performing transshipments between customers so as to further reduce the overall cost. We present a formulation that allows transshipments, either from the supplier to customers or between customers. We also propose an adaptive large neighborhood search heuristic to solve the problem. This heuristic manipulates vehicle routes while the remaining problem of determining delivery quantities and transshipment moves is solved through a network flow algorithm. Our approach can solve four different variants of the problem: the IRP and the IRPT, under maximum level and order-up-to level policies. We perform an extensive assessment of the performance of our heuristic.     

Fuzzy inference systems and inventory allocation decisions: Exploring the impact of priority rules on total costs and service levels

Inventory allocation decisions in a distribution system concern issues such as how much and where stock should be assigned to orders in a supply chain. When the inventory level of an inventory point is lower than the total number of items ordered by lower echelons in the chain, the decision of how many items to allocate to each ``competing'' order must take into consideration the trade-off between cost and service level. This paper proposes a decision-support system that makes use of fuzzy logic to consider inventory carrying, shortage and ordering costs as well as transportation costs. The proposed system is compared through simulation with three other inventory allocation decision support models in terms of cost and service levels achieved. Conclusions are then drawn.     

Using robust optimization for distribution and inventory planning for a large pulp producer

Södra Cell is a world leading producer of pulp and has a large distribution network for its pulp products. This network includes production mills in Sweden and Norway, terminals in European harbours and inland locations, and many customers. The company uses several transport modes including long chartered vessels, spot vessels, trains, barges and trucks. The company uses a supplier managed inventory with a large proportion of its customers. This makes the logistic planning including transportation and inventory critical, as Södra Cell has direct responsibility of their customers’ inventories. However, there is still some uncertainty regarding customer demand and Södra Cell has traditionally used a safety stock inventory approach to handle this. In this paper, we introduce a robust optimization approach to handle the uncertainty and to establish a distribution plan, together with related inventory management. With this approach there is no need for explicit safety stock levels. This is instead taken into account directly through the robust solution. In the proposed model, we can use practical characterization and historical information on the uncertainty. An important result with this is that we can avoid solutions that are too conservative and costly as in standard robust models. A large case study from Södra Cell is used to validate the proposed approach against the traditional approach with safety stock. The analysis is based on simulations and it shows that the robust approach is more cost efficient and can be used as a basis in a decision support system.     

Understanding the role of an IT artifact in online service continuance: An extended perspective of user satisfaction

Given increasing investment in an IT (information technology) artifact (i.e., online service website), it is becoming important to retain existing customers. In order to help link website design and investment decisions to the strategy for retaining customers, we propose a model by extending the user satisfaction perspective into research on online service continuance. We empirically tested the model within the context of a social network service. The analysis results found that website information satisfaction and system satisfaction play key roles in forming continuance intention through perceived usefulness and perceived enjoyment. It is also noted that computer anxiety serves as an important moderator toward continuance intention. Theoretical and practical implications are offered for better understanding of the role of the IT artifact in online service post-adoption phenomena.     

An integrated inventory problem with transportation in a divergent supply chain under service level constraint

This study investigates an integrated inventory problem with transportation in a single-vendor and multi-buyer divergent supply chain. The vendor manufactures a product and delivers the product to the buyers located in different locations by a fleet of vehicles of identical capacity. The external demands per unit time on the buyers are independent and normally distributed. The lead time components of the buyers, excluding transportation time, can be reduced at an added crash cost. A model has been formulated to minimize the total expected cost of the system associated with the production, inventory, transportation and lead time reduction to find the optimal production, inventory and routing decisions while satisfying the service level constraint of the buyers. We propose a coordinated two-phase iterative approach to solve the model, which has been illustrated through a numerical example.     

An inventory replenishment policy for deteriorating items with shortages and partial backlogging

It has long been assumed that the shortages in inventory systems are either completely backlogged or totally lost. However, it is more reasonable to characterize that the longer the waiting time for the next replenishment, the smaller the backlogging rate would be. Moreover, the opportunity cost due to lost sales should be considered since some customers would not like to wait for backlogging during the shortage periods. Without considering these two realistic conditions, study on the inventory modeling for deteriorating items with shortages and partial backlogging cannot be complete and general. In the present article we define an appropriate time-dependent partial backlogging rate and introduce the opportunity cost due to lost sales. Numerical examples are also presented to illustrate the effects of changes in backlogging parameter and unit opportunity cost on total cost and the optimal number of replenishments.Scope and purposeIn a recent article published in this Journal, Giri et al. (Comput. Oper. Res. 27 (2000) 495–505) implemented an existing procedure to the inventory problem of Hariga and Al-Alyan (Comput. Oper. Res. 24 (1997) 1075–83) which concerns with lot-sizing heuristic for deteriorating items with shortages allowed in all cycles except the last one. Giri et al. deviated from the traditional practice and suggested a new policy allowing shortages in all cycles over a finite planning horizon. Their numerical results indicated the proposed policy is cheaper to operate with a cost reduction up to 15%. However, they did not consider the opportunity cost due to lost sales that happen because customers would not like to wait for backlogging. Moreover, for many products with growing sales, the length of the waiting time for the next replenishment is the main factor for determining whether the backlogging will be accepted or not, and the backlogging rate is expected to be time-dependent. Thus the assumption made in Giri et al. that the backlogging rate is a fixed fraction of the total amount of shortages is not reasonable.The purpose of this paper is to present a more realistic discussion of the inventory problem for deteriorating items with time-varying demands and shortages over a finite planning horizon. In contrast to the model by Giri et al., we define an appropriate partial backlogging rate and introduce the opportunity cost due to lost sales. We attempt to complement their model as a practical and general solution for inventory replenishment problems. With these extensions, the scope of applications of the present results is expanded.     

Fuzzy opportunity cost for EOQ model with quality improvement investment

The cost of capital (i.e. opportunity cost) is one of the key factors that will influence the inventory and investment decisions. Previously, the classical EOQ model has been extended to include an imperfect production process and quality improvement investment, where the opportunity cost rate (interest rate or discounted rate) for evaluating the cost of capital investment is known with certainty. However, in some practical situations, the opportunity cost rate probably incurs disturbance due to the unstable environments. To capture this reality, this paper attempts to combine the statistical technique and fuzzy sets concept to deal with the unstable opportunity cost rate, so as to modify the aforementioned inventory/investment model. We derive the optimal lot size and the optimal process quality level in the fuzzy sense utilizing the logarithmic investment cost function. A numerical example is provided, and the results are compared with those obtained from a crisp opportunity cost rate model.     

A multi-server perishable inventory system with negative customer

In this paper, we consider a continuous review perishable inventory system with multi-server service facility. In such systems the demanded item is delivered to the customer only after performing some service, such as assembly of parts or installation, etc. Compared to many inventory models in which the inventory is depleted at the demand rate, however in this model, it is depleted, at the rate at which the service is completed. We assume that the arrivals of customers are according to a Markovian arrival process (MAP) and that the service time has exponential distribution. The ordering policy is based on (s, S) policy. The lead time is assumed to have exponential distribution. The customer who finds either all servers are busy or no item (excluding those in service) is in the stock, enters into an orbit of infinite size. These orbiting customers send requests at random time points for possible selection of their demands for service. The interval time between two successive request-time points is assumed to have exponential distribution. In addition to the regular customers, a second flow of negative customers following an independent MAP is also considered so that a negative customer will remove one of the customers from the orbit. The joint probability distribution of the number of busy servers, the inventory level and the number of customers in the orbit is obtained in the steady state. Various measures of stationary system performance are computed and the total expected cost per unit time is calculated. The results are illustrated numerically.     

Replenishment policy based on modified ant colony optimisation and statistical analysis under the pre-order penetration point

In the supply chain, most businesses in the pre-order penetration point (pre-OPP) operate under the forecast-driven mode, so that the decisions regarding inventory are made in accordance with the forecast and replenishment planning. This paper considers the stochastic dynamic lot-sizing problem of the two-phased transportation cost, service level constraint, and cash flow under a non-deterministic demand. This problem includes a nonlinear integer programming sub-problem. Therefore, this paper proposes an optimisation replenishment policy method based on modified ant colony optimisation (ACO) and response surface methodology. The main differences between the modified ACO and the traditional ACO lie in the modified update of pheromone intensity and the dynamic mutation operator. The experimental result shows that when the demand is normal distribution, the proposed approach, successfully finds the stationary point of minimum response. Besides, in the test of the algorithm solution quality, the modified ACO is better than the traditional ACO in all scenarios.     

一种考虑相关需求的多级库存控制优化模型

在技术驱动的全球化市场,供应链管理已经成为企业和学者共同面对的重要课题。库存控制问题则是企业供应链管理中一个很重要的环节。该文研究了在供应链管理的环境下,由K个配送中心,每个配送中心由Nk个零售商组成的配送网络的库存控制问题。凭着对实际配送系统的观察和分析,在综合考虑了同一产品在不同零售点需求的相关性,以及同一产品在不同周期需求相关性的情况下,以最小化库存成本和运输成本之和为目标,一定的服务水平为约束,建立了多级库存控制优化模型。     

Modelling and analysis of inventory replenishment for perishable agricultural products with buyer–seller collaboration

In this article, we study the inventory replenishment model for perishable agricultural products in a simple two-level supply chain. Collaborative forecasting is introduced into the inventory replenishment decisions to avoid overstocking and understocking of agricultural products, and to maximise profits. We analyse the model with ordering cost, holding cost, shortage cost, deterioration cost and opportunity lost cost of perishable agricultural products. Extensive numerical analysis is carried out to study the performance of the inventory policy. The optimal replenishment policy that minimises the total cost can be obtained from the model. It has demonstrated that the supply chain cost decreases with supplier and retailer's collaborative forecasting.     

多级多商品流物流网络设计的优化模型与组合模拟退火算法*

以最小化系统内的建设费用、库存费用和运输费用为优化目标,建立可描述一般性带能力约束的多级多商品流物流网络设计问题的优化模型,并根据物流网络设计问题的特点,基于模拟退火算法的思想,设计组合模拟退火算法对模型进行求解。算例的计算结果表明,该优化方法运算快捷,结果正确合理,能为此类物流网络设计问题提供科学的决策依据;通过分析发现,存储费用和运输费用都会影响物流网络系统的总费用,但运输费用对系统总费用的影响程度相对要大得多。     

Which is more important in Internet shopping,perceived price or trust?

Price and trust are considered to be two important factors that influence customer purchasing decisions in Internet shopping. This paper examines the relative influence they have on online purchasing decisions for both potential and repeat customers. The knowledge of their relative impacts and changes in their relative roles over customer transaction experience is useful in developing customized sales strategies to target different groups of customers. The results of this study revealed that perceived trust exerted a stronger effect than perceived price on purchase intentions for both potential and repeat customers of an online store. The results also revealed that perceived price exerted a stronger influence on purchase decisions of repeat customers as compared to that of potential customers. Perceived trust exerted a stronger influence on purchase decisions of potential customers as compared to that of repeat customers.     

基于椭圆曲线群签名方案的多银行电子现金系统

电子现金系统是一种非常重要的电子支付方式,如何通过群签名确保电子现金系统的安全、高效支付一直是国内外研究的重点.对已提出的椭圆曲线群签名方案进行改进,解决原方案中存在的一个安全问题,并给出成员撤销算法,最后基于改进后的群签名方案提出一个多银行电子现金系统,该系统能够防止用户篡改电子现金的金额、防止敲诈、洗钱和非法购买,同时可以撤销成员的匿名性并灵活地实现成员撤销.     

Decomposition heuristic to minimize total cost in a multi-level supply chain network

In this paper, the distribution planning model for the multi-level supply chain network is studied. Products which are manufactured at factory are delivered to customers through warehouses and distribution centers for the given customer demands. The objective function of suggested model is to minimize logistic costs such as replenishment cost, inventory holding cost and transportation cost. A mixed integer programming formulation and heuristics for practical use are suggested. Heuristics are composed of two steps: decomposition and post improving process. In the decomposition heuristics, the problems are solved optimally only considering the transportation route first by the minimum cost flow problem, and the replenishment plan is generated by applying the cost-saving heuristic which was originally suggested in the manufacturing assembly line operation, and integrating with the transportation plan. Another heuristic, in which the original model is segmented due to the time periods, and run on a rolling horizon based method, is suggested. With the post-improving process using tabu search method, the performances are evaluated, and it was shown that solutions can be computed within a reasonable computation time by the gap of about 10% in average from the lower bound of the optimal solutions.     

集成整车物流系统的网络规划问题研究

综合考虑运输、库存、设施、服务质量等决策因素,建立了整车物流网络规划集成优化模型,针对由工厂、集货中心和分销中心构成的基本物流网络,提出了用于运输路径优化的流预测算法,并嵌入到遗传算法,解决了适应值的计算难点,给出了基于流预测的遗传算法求解框架．通过实例分析了运输规模效应、库存控制策略、服务质量指标等因素对物流网络结构设计方案的影响。     

A joint model for cash and inventory management for a retailer under delay in payments

As retail companies continue to navigate through the economy downturn, it becomes critical to find innovative cost reduction methods. Cash management is a cost-intensive process for retailers, who are currently focusing on effective cash management, such as deciding on the maximum cash level to keep in their business accounts and how much to borrow to finance inventories and pay suppliers. In this paper, we consider the problem of finding the optimal operational (how much to order and when to pay the supplier) and financial decisions (maximum cash level and loan amount) by integrating the cash management and inventory lot sizing problems. We consider a supplier offering a retailer an interest-free credit period for settling the payment. Beyond this period, the supplier charges interest on the outstanding balance. Whenever the cash exceeds a certain limit, it will be invested in purchasing financial securities. At the time when the retailer pays the supplier for the received order, cash is withdrawn from the account, incuring various financial costs. If the cash level becomes zero or not sufficient, the retailer obtains an asset-based loan at interest. We model this problem as a nonlinear program and propose a solution procedure for finding the optimal solution. We perform a numerical study to analyze the impact of optimal cash management on the inventory decisions. The results indicate that the optimal order quantity decreases as the retailer’s return on cash increases. We compare our model to a model that ignores financial considerations of cash management, and show numerically that our model lowers the retailer’s cost. Also, we illustrate the effect of changing various model parameters on the optimal solution and obtain managerial insights.     

The lot size-reorder level inventory system with customers impatience functions

In this paper, we study a continuous review inventory model with deterministic demand. The model allows shortages, which are partially backlogged. The backlogging is characterized using an approach in which customers are considered impatient. Total profit function is developed using three general costs: holding cost, order cost and shortage cost. Holding cost is based on average stocks and order cost is fixed per replenishment. In shortage cost, we include three significant costs: the unit backorder cost (depending on the shortage time), the goodwill cost (constant) and the opportunity cost. A general approach is presented to determine the economic lot size, the reorder level and the minimum total inventory cost. We consider two customers impatience functions to illustrate the application of the procedure. This paper extends several models studied by other authors.