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Companies increasingly employ dual-channeling strategies with online and offline channels to reach customers. The combination of high return rates in e-commerce and the possibility for customers to return products ordered online at any offline store may result in unbalanced inventories. Transshipments can be used to deal with these unbalanced inventories. In this paper we study dynamic policies for transshipment of products that are returned cross-channel from online to offline stores. At the end of each period in a finite sales season, cross-channel returned products can be transshipped back to the online store or kept on-hand at the offline store. Optimal transshipment policies are obtained using a Markov decision process. We introduce a well-performing heuristic based on the expected costs during the sales season, with a maximum deviation of 1.59 % from the optimal costs in experiments. Furthermore, we show that in all instances our heuristic outperforms static policies in which products are either always or never shipped back to the online store. We observe that dynamic transshipment policies are more effective than static policies in dealing with imbalances in the initial stock. Dynamic transshipment of cross-channel returns seems to open up possibilities for more effective demand fulfillment of dual-channel companies.

Various rental systems, such as public libraries and tool rental companies, have a support warehouse for storing rental products at low cost and carrying out expedited shipments in response to stock-outs at local warehouses. In case of stock-outs, rental systems commonly employ partial backordering, i.e., a limited number of demands is backordered while additional demand is lost. We include partial backordering in our models and demonstrate its relevance. We fully characterize costs and optimal base stock policies in cases with one support and one local warehouse and provide upper bounds for base stock levels in the general system. By enumerating base stock policies and evaluating exact costs numerically, we determine optimal base stock policies for small systems with up to six local warehouses. For larger systems we develop a greedy algorithm based on approximate cost evaluations. The resulting base stock policies have costs within 0.2% from optimality on average in experiments. Among other things, experiments indicate that existing methods with no backordering may lead to poor solutions with partial backordering and that partial backordering is an effective means to reduce lost demand even with limited partial backorder levels. (C) 2017 Elsevier B.V. All rights reserved.

The highly variable demand of fast fashion causes retailers in the industry to face large uncertainties when allocating initial inventory batches across multiple locations. Further into the selling season, inventory imbalances might arise as an effect of deviations from expected demand. To mitigate these imbalances, retailers can make use of lateral transshipments of inventory from locations with excess stock to those facing the risk of a stockout. Such transshipments require models for determining what and how much to ship as well as when to ship it. This thesis investigates how such a model can be applied on replenishment warehouse level in a fast-fashion retail setting. The research was conducted through a quantitative case study at Hennes & Mauritz (H&M), one of the largest fast-fashion retailers in the world. An appropriate existing transshipment model based on the concept of service level was identified and adjusted to suit the characteristics of H&M. In contrast to the vast majority of models in literature, empirical probability distributions were used for dynamically modelling short-term demand. The proposed model was evaluated and found to suggest transshipments yielding significant revenue increase driven by lowered price reductions. This thesis differs from existing literature by providing a unique case-study of how a transshipment model can be applied in practice and how it performs on empirical data from one of the largest fast-fashion retailers in the world. Den kraftigt varierande efterfrågan på snabbt mode gör att aktörer i branschen står inför stora osäkerheter vid initiala lagerallokeringar. Längre in i försäljningscykeln kan lagerobalanser uppstå till följd av avvikelser från den förväntade efterfrågan. För att hantera obalanserna kan företag flytta lager från de regioner med lageröverskott till de som i närtid riskerar att få slut i lager. Sådana flyttar kräver modeller för att avgöra vad och hur mycket som ska flyttas samt när det ska flyttas. Detta examensarbete undersöker hur en sådan modell kan appliceras inom branschen för snabbt mode. Studien genomfördes som en kvantitativ fallstudie i samarbete med Hennes & Mauritz (H&M), en av världens största aktörer inom snabbmodebranschen. En lämplig existerande modell som baseras på konceptet om servicenivå identifierades och anpassades efter H&M:s egenskaper. Till skillnad från majoriteten av modeller i literature användes empiriska sannolikhetsfördelningar för att dynamiskt modellera kortsiktig efterfrågan. Den föreslagna modellen utvärderades och visades föreslå flyttar som genererar signifikanta intäktsökningar drivet av lägre prisnedsättningar. Denna studie skiljer sig från existerande litteratur genom sitt bidrag med en unik fallstudie av hur en modell för lagerflyttar kan appliceras i praktiken samt hur den presterar på empirisk data från en av världens största snabbmodeaktörer.

We consider a multi-item spare parts problem with multiple warehouses and two customer classes, where lateral transshipments are used as a differentiation tool. Specifically, premium requests that cannot be met from stock at their preferred warehouse may be satisfied from stock at other warehouses (so-called lateral transshipments). We first derive approximations for the mean waiting time per class in a single-item model with selective lateral transshipments. Next, we embed our method in a multi-item model minimizing the holding costs and costs of lateral and emergency shipments from upstream locations in the network. Compared to the option of using only selective emergency shipments for differentiation, the addition of selective lateral transshipments can lead to significant further cost savings (14% on average). ?? 2014 Elsevier B.V. All rights reserved.

Library customers can soon order books online and specify a location to collect them from. Libraries exchange books between locations to meet these requests. Two types of exchanges take place: transshipments from library to library to fulfill the requests and rebalancing to redistribute books between libraries. This research determines optimal decisions for transshipments and rebalancing, so that logistic costs in the library system are minimized. In current practice, libraries typically send the book back to the original library after return. We consider a more general policy, in which we rebalance books in anticipation of demand. Moreover, we determine the optimal location from which to transship a book when it is unavailable at the location of demand. By means of stochastic dynamic programming, we derive the optimal policy for small instances. For larger instances we present two heuristics: the cluster and the expected shortage reduction (ESR) heuristic. The ESR heuristic proves to be near-optimal and significantly outperforms current practice. (C) 2013 Elsevier B.V. All rights reserved.

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 satisfied from stock on hand. The elements of an inventory system considered, e.g. size, cost structures and service level definition, all influence the best method of transshipping. Models of many different systems have been considered. This paper provides a literature review which categorizes the research to date on lateral transshipments, so that these differences can be understood and gaps within the literature can be identified. (C) 2010 Elsevier B.V. All rights reserved.

Lateral transshipments are a method of responding to shortages of stock in a network of inventory-holding locations. Conventional reactive approaches only seek to meet immediate shortages. The study proposes hybrid transshipments which exploit economies of scale by moving additional stock between locations to prevent future shortages in addition to meeting immediate ones. The setting considered is motivated by retailers who operate networks of outlets supplying car parts via a system of periodic replenishment. It is novel in allowing non-stationary stochastic demand and general patterns of dependence between multiple item types. The generality of our work makes it widely applicable. We develop an easy-to-compute quasi-myopic heuristic for determining how hybrid transshipments should be made. We obtain simple characterizations of the heuristic and demonstrate its strong cost performance in both small and large networks in an extensive numerical study.

In managing an inventory network, two approaches to the pooling of stock have been proposed. Reactive transshipments respond to shortages at a location by moving inventory from elsewhere within the network, while proactive stock redistribution seeks to minimize the chance of future stockouts. This paper is the first to propose an enhanced reactive approach in which individual transshipments are viewed as an opportunity for proactive stock redistribution. We adopt a quasi-myopic approach to the development of a strongly performing enhanced reactive transshipment policy. In comparison to a purely reactive approach to transshipment, service levels are improved while a reduction in safety stock levels is achieved. The aggregate costs incurred in managing the system are significantly reduced, especially so for large networks. Moreover, an optimal policy is determined for small networks and it is shown that the enhanced reactive policy substantially closes the gap to optimality. (C) 2012 Elsevier B.V. All rights reserved.

In managing networks of stock holding locations, two approaches to the pooling of inventory have been proposed. Reactive transshipm nts respond to stockouts at a location by moving inventory from elsewhere within the network, while proactive redistribution of stock seeks to minimise the chance of future shocks. This paper is the first to propose a hybrid approach in which transshipments are viewed as an opportunity for stock redistribution. We adopt a quasi-myopic approach to the development of a strongly performing hybrid transshipment policy. Numerical studies which utilise dynamic programming and simulation testify to the benefits of using transshipments proactively. In comparison to a purely reactive approach to transshipment, service levels are improved while a reduction in safety stock levels is achieved. The aggregate costs incurred in managing the system are significantly reduced, especially so for large networks facing high levels of demand.

In managing networks of stock holding locations, two approaches to the pooling of inventory have been proposed. Reactive transshipm nts respond to stockouts at a location by moving inventory from elsewhere within the network, while proactive redistribution of stock seeks to minimise the chance of future shocks. This paper is the first to propose a hybrid approach in which transshipments are viewed as an opportunity for stock redistribution. We adopt a quasi-myopic approach to the development of a strongly performing hybrid transshipment policy. Numerical studies which utilise dynamic programming and simulation testify to the benefits of using transshipments proactively. In comparison to a purely reactive approach to transshipment, service levels are improved while a reduction in safety stock levels is achieved. The aggregate costs incurred in managing the system are significantly reduced, especially so for large networks facing high levels of demand.

Inventory redistribution and emergency replenishment in supply chains have long been studied in various contexts. From our strategic perspective, both systems can be used alternatively to cope with product shortages in a supply chain, especially for situations where high shortage costs are involved. In this paper, we present an incorporated scheme of lateral transshipments and emergency orders in a multi-location inventory system. We focused on a complex distribution network consisting of a capacitated distribution center and multiple retailers. A mathematical model is formulated in order to determine optimal inventory policies of the integrated systems. Lastly, we proposed a solution methodology using a hybrid Genetic Algorithm to solve the integrated multi-location inventory problem.