Multi-item inventory control with full truckloads : a comparison of aggregate and individual order triggering

In this paper we consider the stochastic joint-replenishment problem in an environment where transportation costs are dominant and full truckloads or full container loads are required. One replenishment policy, taking into account capacity restrictions of the total order volume, is the so-called QS policy, where replenishment orders are placed to raise the individual inventory positions of all items to their order-up-to levels, whenever the aggregate inventory position drops below the reorder level. We first provide a method to compute the policy parameters of an QS policy such that item target service levels can be met, under the assumption that demand can be modeled as a compound renewal process. The approximate formulas are based on renewal theoretic results and are tested in a simulation study, revealing a good performance. Second, we compare the QS policy with a simple allocation policy, where replenishment orders are triggered by the individual inventory positions of the items. At the moment when an individual inventory position drops below its item reorder level a replenishment order is triggered and the total vehicle capacity is allocated among all items such that the expected elapsed time before the next replenishment order is maximized. In an extensive simulation study it is illustrated that the QS policy outperforms this allocation policy, standing for lower inventory levels to obtain the same service level. While for identical items the difference between the performance of both policies is negligible, differences can be large for different item characteristics

Inventory redistribution for fashion products under demand parameter update

Demand for fashion products is usually highly uncertain. Often, there is only one possibility for procurement before the selling season. In order to improve the traditional newsvendor-type overage-underage trade-off we study a network of two expected profit maximizing retailers selling a fashion product where there is an additional opportunity for redistribution of stock during the selling season. We distinguish between the situation where redistribution is done at the moment when one of the retailers is running out of stock and the situation where the redistribution time is already determined and fixed before the selling season. We model the demand process at a retailer by a Poisson Process with an uncertain mean and use a Bayesian approach to update the distribution parameters before transshipments are done. In a numerical study we compare the different policies and show that timing flexibility and updating are especially beneficial in situations with low profit margins and high parameter uncertainty. Further, we show that depending on the instance, an optimal predetermined transshipment timing depends on the problem parameters and may be between the middle and the end of the selling season

Analysis of a two-echelon inventory system with two supply modes

In this paper, we consider a serial two-echelon periodic review inventory system with two supply modes at the most upstream stock point. As control policy for this system, we propose a natural extension of the dual-index policy, which has three base-stock levels. We consider the minimization of long run average inventory holding, backlogging, and both per unit and fixed emergency ordering costs. We provide nested newsboy characterizations for two of the three base-stock levels involved and show a separability result for the difference with the remaining base-stock level. We use results for the single-echelon system to efficiently approximate the distributions of random variables involved in the newsboy equations and find an asymptotically correct approximation for both the per unit and fixed emergency ordering costs. Based on these results, we provide an algorithm for setting base-stock levels in a computationally efficient manner. In a numerical study, we investigate the value of dual-sourcing in supply chains and show that it is useful to decrease upstream stock levels. In cases with high demand uncertainty, high backlogging cost or long lead times, we conclude that dual-sourcing can lead to significant savings

Monotonicity and supermodularity results for the Erlang loss system

For the Erlang loss system with s servers and offered load a, we show that: (i) the load carried by the last server is strictly increasing in a; (ii) the carried load of the whole system is strictly supermodular on f(s; a)js = 0; 1; : : : and a > 0g

Single item inventory control under periodic review and a minimum order quantity

In this paper we study a periodic review single item single stage inventory system with stochastic demand. In each time period the system must order none or at least as much as a minimum order quantity Qmin. Since the optimal structure of an ordering policy with a minimum order quantity is complicated, we propose an easy-to-use policy, which we call (R, S,Qmin) policy. Assuming linear holding and backorder costs we determine the optimal numerical value of the level S using a Markov Chain approach. In addition, we derive simple news-vendor-type inequalities for near-optimal policy parameters, which can easily be implemented within spreadsheet applications. In a numerical study we compare our policy with others and test the performance of the approximation for three different demand distributions: Poisson, negative binomial, and a discretized version of the gamma distribution. Given the simplicity of the policy and its cost performance as well as the excellent performance of the approximation we advocate the application of the (R, S,Qmin) policy in practice

Analysis of an assemble-to-order system with different review periods

We consider a single item assembled from two components. One of the components has a long leadtime, high holding cost and short review period as compared to the other one. We assume that net stocks are reviewed periodically, customer demand is stochastic and unsatisfied demand is back ordered. We analyze the system under two different policies and show how to determine the policy parameters minimizing average holding and backorder costs. First, we consider a pure base stock policy, where orders for each component are placed such that the inventory position is raised up to a given base stock level. In contrast to this, only the orders for one component follow this logic while the other orders are synchronized in case of a balanced base stock policy. Through mathematical analysis, we come up with the exact long-run average cost function and we show the optimality conditions for both policies. In a numerical study the policies are compared and the results suggest that the balanced base stock policy works better than the pure base stock policy under low service levels and when there is a big difference in the holding costs of the components

Biocompatibility Evaluation of Engineered Amino Acid Pairing Peptides for Drug Delivery

To ensure the effective and safe use of nanomaterials for medical applications, the biocompatibility of the materials must be tested with particular relevance to the environment in which the material is placed. In nanoparticle-based drug delivery, it is crucial to evaluate a nanoparticle’s biocompatibility to ensure minimal cytotoxicity. Of several types of nanoparticles, peptide-based nanoparticles have emerged as promising systems for targeted cancer therapy. Yet, the biocompatibility of many of these peptides and their assembled particles has not been studied. This thesis, summarizes the original contribution on the effective and safe use of the particular self/co-assembling, amino acid pairing peptides and some of their DEGylated forms (modified versions) as carriers for anticancer drug delivery application. Therefore, the biocompatibility of the self-assembling, amino acid pairing (AAP) peptides AC8, its two DEGylated forms, as well as two related peptides, EAK16-II and EK8, is systematically investigated. The toxicity of these peptides and their complexes with pirarubicin was tested against the human adenocarcinoma lung cancer cell line, A549.The biocompatibility of the peptide-drug co-assembling complexes is assessed and the potential of these five peptides as carriers for the hydrophobic anticancer drug pirarubicin is demonstrated. For the first time experimental results on cytotoxicity, haemolytic activity, red blood cell (RBC) aggregation, complement activation and anaphylotoxin activation as an end result of complement activity for these five AAP peptides is reported. AC8, the amino end DEGylated AC8 (NP-I) and EK might be strong candidates for hydrophobic drug delivery considering their lack of toxicity and the fact that they are not recognized as a foreign molecule, inducing no considerable immune reactions. These results provide a basis for in vivo experiments and predict minimal in vitro toxicity of these peptides based delivery systems.1 yea

Inventory models with lateral transshipments : a review

Lateral transshipments within an inventory system are stock movements between locations of the same echelon. These transshipments can be conducted periodically at predetermined points in time to proactively redistribute stock, or they can be used reactively as a method of meeting demand which cannot be satised from stock on hand. The elements of an inventory system considered, e.g. size, cost structures and service level denition, all in uence the best method of transshipping. Models of many dierent systems have been considered. This paper provides a literature review which categorizes the research to date on lateral transshipments, so that these dierences can be understood and gaps within the literature can be identied

A multi-item periodic replenishment policy with full truckloads

In this paper we consider a stochastic multi-item inventory problem. A retailer sells multiple products with stochastic demand and is replenished periodically from a supplier with ample stock. At each order instant it is decided which product to order and how much to order. For the delivery of the products trucks with a finite capacity are available. The dispatched trucks arrive at the retailer after a constant leadtime and with each truck fixed shipping costs are charged independent on the number of units shipped. Additionally, linear holding and backorder costs at the end of a review period are considered. Since fixed transportation costs are high coordination of orders and full truckload shipments can benefit from economies of scale. We propose a dynamic order-up-to policy where initial ordersizes can be reduced as well as enlarged to create full truckloads. We show how to compute the policy parameters and in a detailed numerical study we compare our policy with a lower bound and an uncoordinated periodic replenishment policy. An excellent cost performance of the proposed policy can be observed when average time between two shipments is not too large and fixed shipping costs are high

Multi-item inventory control with full truckloads : a comparison of aggregate and individual order triggering

In this paper we consider the stochastic joint-replenishment problem in an environment where transportation costs are dominant and full truckloads or full container loads are required. One replenishment policy, taking into account capacity restrictions of the total order volume, is the so-called QS policy, where replenishment orders are placed to raise the individual inventory positions of all items to their order-up-to levels, whenever the aggregate inventory position drops below the reorder level. We first provide a method to compute the policy parameters of an QS policy such that item target service levels can be met, under the assumption that demand can be modeled as a compound renewal process. The approximate formulas are based on renewal theoretic results and are tested in a simulation study, revealing a good performance. Second, we compare the QS policy with a simple allocation policy, where replenishment orders are triggered by the individual inventory positions of the items. At the moment when an individual inventory position drops below its item reorder level a replenishment order is triggered and the total vehicle capacity is allocated among all items such that the expected elapsed time before the next replenishment order is maximized. In an extensive simulation study it is illustrated that the QS policy outperforms this allocation policy, standing for lower inventory levels to obtain the same service level. While for identical items the difference between the performance of both policies is negligible, differences can be large for different item characteristics