Events - November 2018

Thursday, November 29, 2018 — 1:00 PM EST

Supervisor

Fatma Gzara

Committee chair

Perry Chou - Chemical Engineering

Examining committee

Fatma Gzara - Management Sciences

Samir Elhedhli - Management Sciences

Houra Mahmoudzadeh - Management Sciences

Ricardo Fukasawa - Combinatorics and Optimization

Tuesday, November 27, 2018 — 2:30 PM EST

This study examines how duration of patent examination is affected by technological diversity of patent applications, using a sample of all pharmaceutical patent applications filed between 1985 and 2017 at China’s State Intellectual Property Office (SIPO). Patent examination is a crucial process to evaluate the patentability of technological inventions. To understand what factors influence patent examination duration can offer strategic insights for both patent applicants and patent system designers.

Monday, November 26, 2018 — 12:00 PM to 1:00 PM EST

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.

Monday, November 19, 2018 — 12:00 PM to 1:00 PM EST

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.

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