3MT final competition
Come watch the finalists of the 3MT faculty-based heats present their research in the 3MT university-wide final competition.
Come watch the finalists of the 3MT faculty-based heats present their research in the 3MT university-wide final competition.
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.
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.
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.
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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.
We present a framework for a class of sequential decision-making problems in the context of max-min bi-level programming, where a leader and a follower repeatedly interact. At each period, the leader allocates resources to disrupt the performance of the follower (e.g., as in defender-attacker or interdiction problems), who in turn minimizes some cost function over a set of activities that depends on the leader’s decision.
In this talk I will present an overview of my research on chronic care services. I will then focus on the problem of care delivery for complex patients, with multiple comorbidities. In this project, we develop a Markov Decision Process framework to manage care for individual patients with multiple chronic conditions through a complex care hub. Complex care provision influences the evolution of Patient Activation Measure (PAM), an indicator for healthy behavior, which affects the evolution of health state of patients.
It is generally well accepted that your position in the social network affects your ability to get information. But how do the network positions of those with whom you interact, influence you? This issue is explored using high dimensional network data. Drawing on theories of social influence and the generalized other, social network analytic and text analytic methods, and data science techniques for big data a series of complex socio-technical situation are assessed.
Cutting and Packing problems are hard combinatorial optimization problems that arise in the context of several manufacturing and process industries or in their supply chains. These problems occur whenever a bigger object or space has to be divided into smaller objects or spaces, so that waste is minimized.