Optimal production planning under diffusion demand pattern

Optimal Production Control of Hybrid Manufacturing/Remanufacturing Failure-Prone Systems under Diffusion-Type Demand

The problem of production control for a hybrid manufacturing/remanufacturing system under uncertainty is analyzed. Two sources of uncertainty are considered: machines are subject to random breakdowns and repairs, and demand level is modeled as a diffusion type stochastic process. Contrary to most of studies where the demand level is considered constant and fewer results where the demand is mode...

Robust Optimization of Multi-Period Production Planning Under Demand Uncertainty

Optimal Inventory Policies under Stochastic Production and Demand Rates

We consider a single stage production-inventory system whose production and demand rates are modulated by an environment process modeled as a finite state Continuous Time Markov Chain (CTMC). When the inventory level reaches zero, an order is placed from an external supplier, and it arrives instantaneously. We derive an Economic Order Quantity (EOQ ) policy that minimizes the long-run average c...

Optimal Dynamic Assortment Planning with Demand Learning

We study a family of stylized assortment planning problems, where arriving customers make purchase decisions among offered products based on maximizing their utility. Given limited display capacity and no a priori information on consumers’ utility, the retailer must select which subset of products to offer. By offering different assortments and observing the resulting purchase behavior, the ret...

The Retail Planning Problem Under Demand Uncertainty

We consider the Retail Planning Problem in which the retailer chooses suppliers, and determines the production, distribution and inventory planning for products with uncertain demand in order to minimize total expected costs. This problem is often faced by large retail chains that carry private label products. We formulate this problem as a convex mixed integer program and show that it is stron...