Blood inventory management: Ordering policies for hospital blood banks under uncertainty

The blood supply chain faces several challenges, such as stochastic demand and supply, the relation between the various stages of the chain, and the intrinsic nature of the product. Blood is a perishable, scarce, and (in most cases) voluntarily supplied product used to perform vital transfusions in patients which increases the pressure of managing its supply chain as efficiently and effectively as possible. For these reasons, it is crucial to have optimized inventory management that allows the availability of the right type of blood product, in the right place, at the right time, and in the right amount while avoiding wastage, especially in hospital blood banks that are the direct link to patients. This work aims to address these challenges with a new two-stage stochastic programming model for defining optimal ordering policies for blood products, considering demand uncertainty. This model minimizes wastage, shortages, and total costs related to blood inventory management, including ABO-substitutions. The model supports hospitals’ tactical-operational decisions of when and how much blood products to order. A case study of a Portuguese hospital is used to validate and show the applicability of the model. By comparing several ordering policies, we show that it is possible to contemplate the decision maker's goals whilst obtaining substantial reductions in terms of wastage and costs. These results allow the definition of an important set of managerial insights.     

允许缺货待补的季节性商品二阶联合库存最优订购策略

针对季节性商品提出了二阶单周期缺货待补联合库存模型,其中假设零售商的库存策略采用报童模型且零售商的需求量服从正态分布。对制造商总利润函数的最优解,提出了充分与必要条件,以期可以简便迅速地获得制造商的最优生产批量以及最优订购周期。最后,通过数值算例及在管理上的含义对必要条件进行了充分的讨论。     

A simple and robust batch-ordering inventory policy under incomplete demand knowledge

Generally, the derivation of an inventory policy requires the knowledge of the underlying demand distribution. Unfortunately, in many settings demand is not completely observable in a direct way or inventory records may be inaccurate. A variety of factors, including the potential inaccuracy of inventory records, motivate managers to seek replenishment policies where the inventory is reviewed periodically and a fixed quantity Q is ordered once the inventory level is found to be under a certain point r. To apply such a policy, however, firms must derive the values r and Q without a clear understanding of the demand distribution. We develop estimators of the first two moments of the (periodic) demand by means of renewal theoretical concepts and a regression-based method, and use these estimators in conjunction with the Power Approximation (PA) method of Ehrhardt and Mosier (1984) to obtain an (r, Q) replenishment policy. The proposed methodology is robust and easy to code into a spreadsheet application. A series of numerical studies are carried out to evaluate the accuracy and precision of the estimators, and to investigate the impact of the estimation on the optimality of the inventory policies. Our experiments indicate that the proposed (r, Q) policy is very close, with regard to the expected total cost per period, to the (s, S) policy obtained via the PA method when the demand process is fully observable and inventory records are accurate.     

A note on a production‐inventory model under stock‐dependent demand,Weibull distribution deterioration,and shortage

Recently, Roy and Chaudhuri presented a production‐inventory model for deteriorating items when the demand rate depends on the instantaneous inventory level and the production rate depends on both stock level and demand. The models without shortages and with shortages were discussed. These models impose continuity constraints on the inventory levels, and consequently the optimization problems so obtained are constrained ones. However, the authors treated them as unconstrained ones.     

A backstepping‐based low‐and‐high gain design for marine vehicles

A backstepping control design for marine vehicles was described in (Marine Control Systems: Guidance, Navigation and Control of Ships, Rigs, and Underwater Vehicles. Marine Cybernetics AS: Trondheim, Norway, 2002). Under a backstepping feedback law, global asymptotic stability of the closed‐loop system can be shown under the assumption of unlimited actuation. This paper addresses the issues that arise in the implementation of a backstepping feedback law by saturating actuators. First, for a given backstepping feedback law, an estimate of the domain of attraction is given for the resulting closed‐loop system under actuator saturation. A high gain component is then constructed and augmented to the original backstepping feedback law. This additional high gain component is shown not to shrink the estimate of the domain of attraction but to possess the ability to improve the closed‐loop response and to reject disturbance. Copyright © 2008 John Wiley & Sons, Ltd.     

A simulation‐based algorithm for optimal pricing policy under demand uncertainty

We propose a simulation‐based algorithm for computing the optimal pricing policy for a product under uncertain demand dynamics. We consider a parameterized stochastic differential equation (SDE) model for the uncertain demand dynamics of the product over the planning horizon. In particular, we consider a dynamic model that is an extension of the Bass model. The performance of our algorithm is compared to that of a myopic pricing policy and is shown to give better results. Two significant advantages with our algorithm are as follows: (a) it does not require information on the system model parameters if the SDE system state is known via either a simulation device or real data, and (b) as it works efficiently even for high‐dimensional parameters, it uses the efficient smoothed functional gradient estimator.     

The effect of inflation‐induced demand and trade credit on ordering policy of exponentially deteriorating and imperfect quality items

This paper develops an inventory model for exponentially deteriorating and imperfect quality items when a trade credit is offered by the supplier. As it has been seen that the changing rates of inflation do not just have an effect on the ordered quantity but they also stimulate the demand for products, so this paper considers the combined effect of inflation, deterioration, imperfect quality and ‘’ trade credit policy on the economic ordering policy using a discounted cash flow (DCF) approach. In the study, mathematical models are derived under two different circumstances, i.e., Case I: When the discount offered by the supplier with a condition of making the payment by a specified period, M₁ is accepted; and Case II: Discount is not taken and instead the payment is made by the end of the full credit period M (M > M₁). Finally, a numerical example demonstrating the applicability of the proposed model has been included.     

针对复杂系统并行模拟问题的并发式多级矩阵重排算法

在解决复杂化工过程优化与模拟问题时,大规模代数差分方程的存在导致大量的计算时间花费在重复求解稀疏大型线性方程组的过程中。随着并行计算和网络技术的发展,为了提高优化或模拟工作的速度,可以通过将非对称矩阵重排为带边块对角形式,从而实现对线性系统的高效并行求解。本文提出一种基于Kernighan-Lin算法的并发式的多层次矩阵重排策略,它以最小化边块为目标,同时保证尽可能小的负荷非平衡性,从而获得好的重排结果。应用该重排策略可以对大型稀疏矩阵进行压缩和并行重排,提高重排算法的效率。在研究过程中应用了基于该技术的并行计算程序对一系列标准矩阵进行了检验,并与一些现有的算法进行了比较,证明了其有效性和可行性。     

A branch‐and‐cut algorithm for the Team Orienteering Problem

The Team Orienteering Problem aims at maximizing the total amount of profit collected by a fleet of vehicles while not exceeding a predefined travel time limit on each vehicle. In the last years, several exact methods based on different mathematical formulations were proposed. In this paper, we present a new two‐index formulation with a polynomial number of variables and constraints. This compact formulation, reinforced by connectivity constraints, was solved by means of a branch‐and‐cut algorithm. The total number of instances solved to optimality is 327 of 387 benchmark instances, 26 more than any previous method. Moreover, 24 not previously solved instances were closed to optimality.     

A frame‐based EM‐simulation for design of LC oscillator with MoM capacitor banks

This article presents a simulation method for the design of a digitally controlled oscillator (DCO). Electromagnetic (EM) simulations are essential and inevitable for modern LC oscillator design. Although EM‐simulators provide high accuracy, the EM‐simulation time is very long when metal‐oxide‐metal (MoM) capacitors are present. The proposed frame‐based EM‐simulation can significantly reduce the EM‐simulation time even in the presence of MoM capacitors without influencing the accuracy. To verify the proposed method, a DCO was fabricated using a 55‐nm CMOS process. Measurements of the DCO are in good agreement with the frame‐based post‐layout simulation results. In addition, the DCO has good performances with a low power consumption of approximately 0.68 mW.     

A learn‐and‐construct framework for general mixed‐integer programming problems

In this paper, we propose a new framework for finding an initial feasible solution from a mixed‐integer programming (MIP) model. We call it learn‐and‐construct since it first exploits the structure of the model and its linear relaxation solution and then uses this knowledge to try to produce a feasible solution. In the learning phase, we use an unsupervised learning algorithm to cluster entities originating the MIP model. Such clusters are then used to decompose the original MIP in a number of easier sub‐MIPs that are solved by using a black box solver. Computational results on three well‐known problems show that our procedure is characterized by a success rate larger than both the feasibility pump heuristic and a state‐of‐the‐art MIP solver. Furthermore, our approach is more scalable and uses less computing time on average.     

A new DEA‐based method for fully ranking all decision‐making units

Abstract: Decision makers always lay great emphasis on performance evaluation upon a group of peer business units to pick out the best performer. Standard data envelopment analysis models can evaluate the relative efficiency of decision‐making units (DMUs) and distinguish efficient ones from inefficient ones. However, when there are more than one efficient DMU, it is impossible to rank all of them solely according to standard efficiency scores. In this paper, a new method for fully ranking all DMUs is proposed, which is based on the combination of each efficient DMU's influence on all the other DMUs and the standard efficiency scores. This method is effective in helping decision makers differentiate all units' performance thoroughly and select the best performer.     

A branch‐and‐bound algorithm for scheduling of new product development projects

In this paper, we consider scheduling problem in a new product development project. Each research and development project consists of a set of activities in which each activity may be executed in several ways. Each way of execution of an activity is a different technology, called an alternative technology, which may fail due to technical risks. In this work, we focus on alternative technologies for scheduling activities to maximize the expected net present value. We assume that the activity payoff is obtained as soon as any single technology is completed successfully. Therefore, we analyze the problem and develop a two‐phase solution procedure, consisting of a branch‐and‐bound algorithm and a recursive search procedure. The efficiency of the proposed algorithm has been evaluated on a set of randomly generated test instances.     

Using an online tool to support school‐based ICT policy planning in primary education

An important step towards the successful integration of information and communication technology (ICT) in schools is to facilitate their capacity to develop a school‐based ICT policy resulting in an ICT policy plan. Such a plan can be defined as a school document containing strategic and operational elements concerning the integration of ICT in education. To write such a plan in an efficient way is challenging for schools. Therefore, an online tool [Planning for ICT in Schools (pICTos)] has been developed to guide schools in this process. A multiple case study research project was conducted with three Flemish primary schools to explore the process of developing a school‐based ICT policy plan and the supportive role of pICTos within this process. Data from multiple sources (i.e. interviews with school leaders and ICT coordinators, school policy documents analysis and a teacher questionnaire) were collected and analysed. The results indicate that schools shape their ICT policy based on specific school data collected and presented by the pICTos environment. School teams learned about the actual and future place of ICT in teaching and learning. Consequently, different policy decisions were made according to each school's vision on ‘good’ education and ICT integration.     

Branch‐and‐bound approach for optima localization in scheduling multiprocessor jobs

We consider multiprocessor task scheduling problems with dedicated processors. We determine the tight optima localization intervals for different subproblems of the basic problem. Based on the ideas of a computer‐aided technique developed by Sevastianov and Tchernykh for shop scheduling problems, we elaborate a similar method for the multiprocessor task scheduling problem. Our method allows us to find an upper bound for the length of the optimal schedule in terms of natural lower bound. As a byproduct of our results, a family of linear‐time approximation algorithms with a constant ratio performance guarantee is designed for the NP‐hard subproblems of the basic problem, and new polynomially solvable classes of problems are found.     

Robust optimal tracking control for multiplayer systems by off‐policy Q‐learning approach

In this article, a novel off‐policy cooperative game Q‐learning algorithm is proposed for achieving optimal tracking control of linear discrete‐time multiplayer systems suffering from exogenous dynamic disturbance. The key strategy, for the first time, is to integrate reinforcement learning, cooperative games with output regulation under the discrete‐time sampling framework for achieving data‐driven optimal tracking control and disturbance rejection. Without the information of state and input matrices of multiplayer systems, as well as the dynamics of exogenous disturbance and command generator, the coordination equilibrium solution and the steady‐state control laws are learned using data by a novel off‐policy Q‐learning approach, such that multiplayer systems have the capability of tolerating disturbance and follow the reference signal via the optimal approach. Moreover, the rigorous theoretical proofs of unbiasedness of coordination equilibrium solution and convergence of the proposed algorithm are presented. Simulation results are given to show the efficacy of the developed approach.     

Scalable model‐based configuration management of security services in complex enterprise networks

Security administrators face the challenge of designing, deploying and maintaining a variety of configuration files related to security systems, especially in large‐scale networks. These files have heterogeneous syntaxes and follow differing semantic concepts. Nevertheless, they are interdependent due to security services having to cooperate and their configuration to be consistent with each other, so that global security policies are completely and correctly enforced. To tackle this problem, our approach supports a comfortable definition of an abstract high‐level security policy and provides an automated derivation of the desired configuration files. It is an extension of policy‐based management and policy hierarchies, combining model‐based management (MBM) with system modularization. MBM employs an object‐oriented model of the managed system to obtain the details needed for automated policy refinement. The modularization into abstract subsystems (ASs) segment the system—and the model—into units which more closely encapsulate related system components and provide focused abstract views. As a result, scalability is achieved and even comprehensive IT systems can be modelled in a unified manner. The associated tool MoBaSeC (Model‐Based‐Service‐Configuration) supports interactive graphical modelling, automated model analysis and policy refinement with the derivation of configuration files. We describe the MBM and AS approaches, outline the tool functions and exemplify their applications and results obtained. Copyright © 2010 John Wiley & Sons, Ltd.     

A mixed resilient‐efficient approach toward blood supply chain network design

Unlike its inherent beneficial attributes, the blood supply chain is very complex due to its uncertain nature and irregular donation besides a high vulnerability to disruptions. In this regard, this study provides a multi‐objective integrated resilient‐efficient model to design a blood supply chain network under uncertainty. To evaluate the efficiency, an augmented form of the data envelopment analysis model is incorporated into the extended model. On the other hand, to improve supply chain resilience, different resiliency measures as optimization tools are introduced and inserted into the considered network. As blood donors have a main role in the blood supply chain, this paper undertakes motivational social aspects to stimulate blood donation for reducing possible shortages. Furthermore, to handle the multi‐objective problem, an interactive fuzzy approach is utilized. Finally, to indicate the applicability of the extended model and its solution approaches, a case study is provided considering realistic data. The results revealed that simultaneously considering all three measures of efficiency, resilience, and cost can assist in improvement of blood supply chain network design and a trade‐off among these three measures can be set by decision maker's preferences.     

Parents,pre‐schoolers and learning with technology at home: some implications for policy

Schemes that seek to ensure that children have access to technology at home have, so far, been aimed at children over the age of 8. However, there is likely to be an increasing policy interest in extending similar schemes to pre‐school children given widespread commitment to the value of early intervention in children's education and family life. We draw on three research studies conducted by the authors to discuss the range of technologies that children encounter at home, the different forms their learning takes and family support for learning. We use these findings to provide starting points for considering the implementation of similar schemes for pre‐school children and their parents in the future, identifying several questions to consider when developing policy on home access to technology for pre‐schoolers: which technologies are most appropriate? Will access to technology at home lead to increased use? What roles do parents play in supporting learning? Which forms of learning are most likely to be promoted?     

A comprehensive note on “Lot‐sizing decisions for deteriorating items with two warehouses under an order‐size‐dependent trade credit”

To reduce inventory and increase sales, the supplier frequently offers the retailer a permissible delay in payments if the retailer orders more than or equal to a predetermined quantity. In 2012, Liao et al. proposed an economic order quantity model for a retailer with two warehouses when the supplier offers a permissible delay linked to order quantity. In this paper, we attempt to overcome some shortcomings of their mathematical model. Then, we apply some existing theoretical results in fractional convex programs to prove that the annual total variable cost is pseudoconvex. Hence, the optimal solution exists uniquely, which simplifies the search for the global minimum solution to a local minimum solution. Finally, we run a couple of numerical examples to illustrate the problem and compare the optimal solutions between theirs and ours.