Inventory stacking with partial information

Inventory control with partial observations and inspections

This project studies optimal inventory control problems whose states are not directly observed. What is observed instead are surrogate measures called signals, which are used to characterize the probability distribution of the state variables. Our project draws upon useful concepts developed for nonlinear filtering and stochastic control to group the problems into two classes. In the first clas...

Stochastic inventory control with partial demand observability

Stacking faults and partial dislocations in graphene

We investigate two mechanisms of crystallographic slip in graphene, corresponding to glide and shuffle generalized stacking faults (GSF), and compute their -curves using Sandia National Laboratories Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). We find evidence of metastable partial dislocations for the glide GSF only. The computed values of the stable and unstable stackin...

Two-Warehouse Inventory Model for Deteriorating Items with Time-Dependent Demand and Partial Backlogging Under Inflation

This paper deals with a two-warehouse inventory model for deteriorating items with time dependent demand and partial backlogging under inflation. It is assumed that deterioration of items follows two-parameter Weibull distribution and demand rate varies exponentially with time. Shortages are allowed and partial backlogging depends on waiting time of next replenishment. A numerical example is pr...

Clustering with Partial Information

The Correlation Clustering problem, also known as the Cluster Editing problem, seeks to edit a given graph by adding and deleting edges to obtain a collection of vertex-disjoint cliques, such that the editing cost is minimized. The Edge Clique Partitioning problem seeks to partition the edges of a given graph into edge-disjoint cliques, such that the number of cliques is minimized. Both problem...