Supervisor: Fatih Erenay
Automatic generation of text is an important topic in natural language processing with applications in tasks such as machine translation and text summarization. In this thesis, we explore the use of deep neural networks for generation of natural language. Specifically, we implement two sequence-to-sequence neural variational models - variational autoencoders (VAE) and variational encoder-decoders (VED).
A Cross-Dock (CD) is a synchronized unit of a supply chain network, used to sort the goods received from inbound trucks (from a warehouse or factory), and load those products to outbound trucks (for delivery of the goods to retail stores in the supply chain network). Most cross-docks use forklifts, and other manual material handling equipment (MHE) to process the goods on pallets received from inbound trucks. Those pallets are sorted and loaded onto outbound trucks.
Frank Safayeni
Selcuk Onay
This paper investigates the impacts of two environmental policies: pollution abatement subsidy and emission tax, on a three-tier supply chain, where the manufacturer distributes via multiple competitive retailers and invests in a pollution abatement technology in manufacturing. The government pursues social welfare maximization, while the manufacturer and retailers are profit driven. We find that the subsidy policy offers the manufacturer greater incentives to abate pollution and yields higher profits for channel members.
Mark Hancock, Management Sciences
Miguel Nacenta, Management Sciences
Is communicating via Skype or other video media equivalent to a face-to-face meeting? We have known for some time that after interacting face-to-face, people can predict the cooperative behaviour of strangers with better-than-chance accuracy. But is this ability affected when communications are mediated by video technology? This study reports four laboratory experiments examining how different communication conditions affect cooperation prediction efficacy.
We compare two models of a multi-server queueing system with state-dependent service rates and return probabilities. In both models, upon completing service, customers are delayed prior to possibly returning to service. In one model, the determination of whether a customer will return occurs immediately upon service completion, at the beginning of the delay. In the other, that determination is made at the end of the delay, capturing the idea that it takes time for the customer’s condition and needs to evolve or assess, before it becomes known whether a return to service is needed.
In this talk, we discuss a discrete-time model where the underlying asset price is subject to stochastic volatility and liquidity for optimal trade execution. This model is an extension of Almgren and Chriss' model. Instead of the mean-variance criterion, we consider the mean-quadratic criterion for choosing the optimal strategy through applications of Markov decision processes. We carry out a numerical analysis by Monte Carlo simulation and provide detailed comparison results under various risk aversion criteria.