A New Two‐Bin Policy for Inventory Systems with Differentiated Demand Classes

This paper analyzes the use of a constant critical level policy for fast-moving items, where rationing is used to provide differentiated service levels to two demand classes (high priority and low priority). The previous work on critical level models, with either a continuous or periodic review policy, has only considered slow-moving items with Poisson demand. In this work, we consider a continuous review (Q, r, C) policy with two demand classes that are modeled through continuous distributions, and the service levels are measured by the probability of satisfying the entire demand of each class during the lead time. We formulate a service level problem as an non-linear problem with chance constraints for which we optimally solve a relaxation obtaining a closed-form solution that can be computed easily. For instances, we tested, computational results show that our solution approach provides good-quality solutions that are on average $$0.3~\%$$0.3% from the optimal solution.

Traditional inventory systems treat all demands of a given item equally. This approach is optimal if the penalty costs of all customers are the same, but it is not optimal if the penalty costs are different for different customer classes. Then, demands of customers with high penalty costs must be filled before demands of customers with low penalty costs. A commonly used inventory policy for dealing with demands with different penalty costs is the critical level inventory policy. Under this policy demands with low penalty costs are filled as long as inventory is above a certain critical level. If the inventory reaches the critical level, only demands with high penalty costs are filled and demands with low penalty costs are backordered. In this article, we consider a critical level policy for a periodic review inventory system with two demand classes. Because traditional approaches cannot be used to find the optimal parameters of the policy, we use a multidimensional Markov chain to model the inventory system. We use a sample path approach to prove several properties of this inventory system. Although the cost function is not convex, we can build on these properties to develop an optimization approach that finds the optimal solution. We also present some numerical results. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008

Patient Demand Management through Prioritized Access with Time Windows Access Protocol

Cognitive Radio networks (CRN) enable cognitive users to use portions of the licensed spectrum of the primary users (PU). Dynamic spectrum access (DSA) is a design aspect that facilitates the transmission of cognitive radio (CR) users over idle channels. In many cases, it is not preferable that CR users to be treated equally. Provisioning quality of service (QoS) to some CR users is a challenge in DSA design. In this situation, The CR user traffic is divided into high and low priority classes. Sub-channel reservation (SCR) scheme is the most traditional scheme to provide priority to CR users in admission. In this paper, a new scheme named “low priority bounding” (LPB) scheme is used to provide QoS for CR users. The LPB scheme provides priority by restricting the number of low priority CR users by a threshold. This scheme maintains a suitable level of service to high priority users (as provided by SCR scheme) while improve the level of service for low priority ones. So the revenue gained from LPB scheme is optimized in comparison with SCR scheme. The impact of LPB scheme in the provided QoS is evaluated in terms of blocking probability, service termination rate, and service completion rate. Simulation results are compared with SCR scheme and it shows that the LPB scheme can significantly improve the revenue gained over the traditional SCR scheme.

Joint optimization of inventory replenishment and rationing policies for an omnichannel store with both in-store and online demands

The subjects for study were all parasuicides admitted to the Regional Poisoning Treatment Centre between 1968 and 1973. The parasuicides were divided into four social class groups: Registrar General's Classes I and II; Class III; Class IV; Class V. The characteristics and disposal of parasuicides from each class were compared. A large number of items showed a significant difference across class. Lower class parasuicides were more often characterised by a variety of social problem items including overcrowding, trouble with the law, debt, unemployment and violence in interpersonal relationships. They were more often diagnosed as personality disorders whereas higher class parasuicides were more likely to be diagnosed as depressive. The latter were also more frequently referred to the R. P. T. C. by a medical agent. For higher class patients, after-care more often took the form of in- or out-patient psychiatric treatment; lower class patients were more commonly recommended for social work on discharge. The association between social class and type of after-care was maintained when the diagnostic groups were considered separately. Patients of higher social class within the categories “personality disorder only”, “depression only”, “depression with personality disorder”, “other psychiatric illness with personality disorder” were markedly more likely to receive a psychiatric referral.

This paper presents a greedy randomized adaptive search procedure (GRASP) for scheduling n jobs on m nonhomogeneous parallel machines with time windows. An additional feature of the problem is that each job falls into one of ρ priority classes. The objective is to maximize the number of jobs scheduled, where a job in a higher priority class has infinitely more value than a job in a lower priority class. The GRASP consists of two phases. The first phase produces feasible solutions by ranking each job with a greedy function and then selecting one at random from a restricted candidate list. The process is repeated until no more jobs can be scheduled. The second phase seeks a local optimum by searching over a series of neighborhoods defined by job insertions and exchanges. The algorithm is compared to a dynamic-programming heuristic that sequentially schedules the jobs in each priority class. Extensive computational results are presented based on data drawn from an application involving the use of communications relay satellites.

This paper presents an approximate analysis of delay performance of a WD/SD optical packet/burst switch equipped with infinite optical buffers. By using M/G/1 model, we give the theoretical expression of delay performance of the switch fabric with/without assignment of priority class to service under fixed/variable packet length. Meanwhile, the results of numerical analysis are presented, too. According to these analyses, we give the following main conclusions: in the switch fabric with variable packet/burst length and no assignment of priority class to service, the mean packet/burst delay appears much smaller than that with fixed packet length; and in the switch fabric with assignment of three priority classes to service, the delay of two kinds of services with lower priority classes appears to bigger than that of service with no assignment of priority class.

In this paper, we simulate allocation policies for a two-stage inventory system that receives perfect advance demand information (ADI) from customers belonging to different demand classes. Demands for each customer class are generated by independent Poisson processes while the processing times are deterministic. All customers in the same class have the same demand lead time (the difference between the due date and the requested date) and back-ordering costs. Each stage in the inventory system follows order-base-stock-policies where the replenishment order is issued upon arrival of a customer order. The problem requires a fast and reliable method that determines the system performance under different policies and ADI. Thus, we employ discrete event simulation to obtain output parameters such as inventory costs, fill rates, waiting time, and order allocation times. A numerical analysis is conducted to identify a reasonable policy to use in this type of system.

Watershed prioritization is a strategic procedure used to delineate the most erosion-prone sub-watersheds. Identifying these critical areas is paramount for the effective allocation of resources and the successful implementation of soil and water conservation measures at the watershed level. However, studies concerning the mountainous watershed of Kiile are limited. In this study, the prioritization of 10 sub-watersheds of the Kiile River was done to identify erosion-prone areas using quantitative morphometric analysis. The watershed and its drainage networks were delineated using ALOS PALSAR 12.5 m resolution DEM in ArcGIS 10.4. For prioritisation, morphometric parameters such as linear, areal, and relief aspects were considered and calculated using standard formulae provided by various hydrologists and geomorphologists. Each morphometric parameter was preliminarily ranked based on its relation with soil erodibility. The final prioritization was done based on the compound value (Cp). The analysis result revealed that SW-8 and SW-5 are the most erosion-prone sub-watersheds with the lowest compound value, indicating greater susceptibility to erosion. Based on the results, the sub-watersheds of the Kiile River were categorised into four priority classes: very high, high, medium, and low. The SW-8 and SW-5 fall under the very high priority class, SW-3, SW-4, SW-6, and SW-9 fall under the high priority class, SW-1, SW-7, and SW-2 fall under the medium priority class, and SW-10 falls under the low priority class. This study significantly contributes to the management of mountainous watersheds and may be useful for decision-makers in sustainably managing and conserving the watershed resources.

This paper discusses an inventory rationing system with a threshold in a relatively stable inventory demand environment. There are two different demand classes in this inventory system, prior demand and secondary demand, distinguished by different shortage cost. The inventory system functions as follow. When the inventory level is above the threshold, demands come from both classes are filled. Once the inventory level falls below the threshold, all demands come from secondary demand class are backordered, only prior demand would be served. Heuristic approach was used to solve the model in this paper, and the optimal order quantity, single inventory cycle time and inventory threshold were given. Compare between inventory system with and without inventory threshold shows the cost advantage of the first system. Sensitivity analysis was performed to give a better understanding of two crucial parameter, inventory threshold and cost saving rate.

Dynamic wavelength selection and delayed burst assignment schemes for Optical Burst Switching networks

This study examines the refugee reallocation problem by modeling it as a two-sided matching problem between countries and refugees. Based on forced hierarchical priority classes, I study two interesting refugee matching algorithms to match refugees with countries. Axioms for fairness measures in resource allocation are presented by considering the stability and fairness properties of the matching algorithms. Two profiles are explicitly modeled---country preferences and forced prioritization of refugee families by host countries. This approach shows that the difference between the profiles creates blocking pairs of countries and refugee families owing to the forced hierarchical priority classes. Since the forced priorities for countries can cause certain refugees to linger in a lower priority class in every country, this study highlights the importance of considering refugees' preferences. It also suggests that a hierarchical priority class-based approach without category-specific quotas can increase countries' willingness to solve the refugee reallocation problem.

Analysis of voice and low-priority data traffic by means of brisk periods and slack periods

We consider a spare parts inventory system controlled by a base-stock policy. We assume several demand classes, where the demands of each class follow a compound Poisson process, and a stochastic replenishment lead-time common to all classes. For this inventory system, we investigate two rationing policies that can be employed when the inventory level is critically low. The first policy is the reservation policy, where a part of the stock is reserved for high priority demand classes, whereas the second one is new, which we call a threshold policy, and accepts demands of a given class until the pipeline stock caused by the particular class (plus the amount of the incoming order) reaches a critical level. On average, for 8% (12%) of all instances, the threshold policy performs better than the reservation policy under the full (partial) lost sales case and when the objective is to minimise the average on-hand inventory subject to fill rate service requirements. Furthermore, in many cases where the reservation policy outperforms the threshold policy, the gap between the two policies is small under both service requirements and total cost minimisation criteria. This suggests that a trade-off between ‘fairness’ and ‘cost’ is required, and that when the performance of two policies are similar, the threshold policy is generally favoured.