A Multiechelon Inventory Problem with Secondary Market Sales

Published version made available in SMU repository with permission of INFORMS, 2014, February 28</p

Optimal control of serial inventory systems with fixed replenishment intervals

We consider a single-item, periodic-review, serial inventory/production system, with linear inventory-holding and penalty costs. To facilitate shipment consolidation and capacity planning, we assume that the system has implemented fixed replenishment intervals; each stage is allowed to order only at given equidistant times. Further, for each stage except the most downstream one, the replenishment interval is assumed to be an integer multiple of the replenishment interval of the next downstream stage. This reflects the fact that the further upstream in a supply chain, the higher setup times and costs tend to be, and thus larger batches are desired. Our model with fixed replenishment intervals is a direct generalization of the serial model of Clark and Scarf (1960). For this generalized model, we prove the optimality of base-stock policies, we derive newsboy equations for the optimal base-stock levels, and we describe an efficient exact solution procedure for the case with mixed Erlang demands. Finally, we present extensions to assembly systems and to systems with a modified fill-rate constraint instead of backorder costs

Stochastic Dynamic Demand Inventory Models with Explicit Transportation Costs and Decisions

Recent supply chain literature and practice recognize that significant cost savings can be achieved by coordinating inventory and transportation decisions. Although the existing literature on analytical models for these decisions is very broad, there are still some challenging issues. In particular, the uncertainty of demand in a dynamic system and the structure of various practical transportation cost functions remain unexplored in detail. Taking these motivations into account, this dissertation focuses on the analytical investigation of the impact of transportation-related costs and practices on inventory decisions, as well as the integrated inventory and transportation decisions, under stochastic dynamic demand. Considering complicated, yet realistic, transportation-related costs and practices, we develop and solve three classes of models: (1) Pure inbound inventory model impacted by transportation cost; (2) Pure outbound transportation models concerning shipment consolidation strategy; (3) Integrated inbound inventory and outbound transportation models. In broad terms, we investigate the modeling framework of vendor-customer systems for integrated inventory and transportation decisions, and we identify the optimal inbound and outbound policies for stochastic dynamic supply chain systems. This dissertation contributes to the previous literature by exploring the impact of realistic transportation costs and practices on stochastic dynamic supply chain systems while identifying the structural properties of the corresponding optimal inventory and/or transportation policies. Placing an emphasis on the cases of stochastic demand and dynamic planning, this research has roots in applied probability, optimal control, and stochastic dynamic programming

Multiple sourcing in single- and multi-echelon inventory systems

This thesis deals with stochastic inventory models that focus on the following two aspects in particular: (i) the coordination of multiple supply sources and (ii) the optimization of the inventory allocation and sizing in multi-echelon systems. Initially, single-echelon inventory models with multiple sourcing and multi-echelon inventory models with single sourcing are analyzed separately. In the former case, the goal is the identification of effective inventory control policies. In the latter case, the focus lies on the development of a new multi-echelon approach, which combines the two major frameworks currently available in the literature. Subsequently, both aspects are integrated into a multi-echelon inventory model with multiple sourcing