This dissertation consists of two distinct lines of research e orts. Chapter 2 proposes a general methodology to seek robust solution to multi-stage stochastic optimization problems. Chapters 3, 4 and 5 all deal with models that arise from inventory management and dynamic pricing. Chapter 2...

Deep neural networks (DNNs) are powerful types of artificial neural networks (ANNs) that use several hidden layers. They have recently gained considerable attention in the speech transcription and image recognition community (Krizhevsky et al., 2012) for their superior predictive properties...

The single-item stochastic lot-sizing problem is to find an inventory replenishment policy in the presence of a stochastic demand under periodic review and finite time horizon. The computational intractability of computing an optimal policy is widely believed and therefore approximation...

Retailers procure inventory by placing purchase orders (POs) with suppliers. POs specify product price, quantity, quality, delivery times, and other aspects of the fulfillment process, such as carton labeling requirements and packaging formats. When servicing an order, a supplier may fail to...

Purchase orders specify many aspects of a fulfillment process, including item quantity, delivery time, carton labeling, bar coding, electronic data interchange, retail ticketing, and others. These fulfillment terms are instrumental for highly optimized retail supply chains employing automation...

Deep neural networks (DNNs) are powerful types of artificial neural networks (ANNs) that use several hidden layers. They have recently gained considerable attention in the speech transcription and image recognition community for their superior predictive properties including robustness to over...

The OSTSC package is a powerful oversampling approach for classifying univariant, but multinomial time series data in R. This vignette provides a brief overview of the oversampling methodology implemented by the package. A tutorial of the OSTSC package is provided. We begin by providing three...

High costs for fossil fuels and increasing installations of intermittent energy sources are imposing major challenges on power grid management. Uncertainty in generation and demand for electric energy require flexible generation capacity and stochastic optimization of generation schedules....