This research studies lateral transshipment of critical medical items that have low demands. Due to the high prices of medical items and their limited shelf lives, the expirations contribute significantly to the current prohibitively high cost of the healthcare system. Lateral transshipment between hospitals in a medical system provides opportunities to reduce the expiration costs. This paper studies the decision rule for lateral transshipment in a two-hospital system and extends the rule for the multiple-hospital cases. The decision rule takes the myopic best action by assuming no transshipments will be performed in the future. Numerical experiments demonstrate significant cost savings and the decision rule has a small gap from the upper bound of the total saving. The savings are more considerable when the difference of demand rates at different locations is large and the life time of the medical item is not too long or too short.

The thesis contributes to the body of knowledge in analyzing and optimizing inventories of multiple stocking locations in a supply chain system. Optimization model is developed for planning inventories with respect to the proposed inventory-pooling strategy. The model is solved under stochastic environment using a Hybrid Genetic Algorithm technique.

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.