Advanced Inventory Management

Advanced Inventory Management

In order to provide an appropriate service level to customers while keeping operational costs as low as possible, companies have to design smart replenishment systems. Carefully designed replenishment/distribution systems would enable them to have the right products in the right place at the right time. Although research on inventory management has been around for decades, it still gets significant attention from the research community, as ensuring product availability at low costs is critical to survive in the ever more complex, global, fierce business environment of today. The literature on Inventory Management is vast, and the group at Zaragoza Logistics Center focuses particularly on developing inventory management strategies and models to increase supply chain value, particularly using stochastic inventory models where randomness could originate from either demand or supply. Specifically, the following models are studied by the Advanced Inventory Management Group at ZLC:

  • Coordination in Replenishment/Distribution in multi-supplier and multi-retailer setting with stochastic demand
  • Optimizing Dynamic Inventory Replenishment and Substitution for Products with Lead Times
  • Inventory Control in Systems with Random Yield
  • Production and Transshipment Management of Manufacturing Facilities
  • Inventory Control for Perishable Items with Random Deals (Promotions)
  • Optimal Rationing Policies for Inventory Systems with Multiple Demand Classes
  • Ordering Policies in the Face of Unreliable Suppliers and Counterfeit Products
  • Optimal Dual Sales and Stock Replenishment by Flexible Contracts in the face of a spot market
  • Inventory Pooling Mechanisms with Information Asymmetry
  • Risk Sharing Contracts

Main Researchers

Dr. Çagri Gurbuz

Professor, MIT-Zaragoza
Research Affiliate, MIT CTL

Dr. Victoria Muerza

Postdoctoral Research Fellow
MIT-Zaragoza

Main Achievements

INSPIRE project: Towards growth for business by flexible processing in customer-driven value chains (2016 – 2018).

NEXTNET project: Next generation Technologies for networked Europe (2017 – 2019).

Related Publications