A number of current and past graduate students of the Department of Management Sciences were recently honoured at the 2018 Canadian Operational Research Society (CORS) annual conference, held June 4-6 in Halifax, Nova Scotia.
We will discuss a few examples from healthcare, where quantitative models embedded in decision-support tools can improve the quality of decision-making (for patients, physicians, or caregivers) and patient outcomes.
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.
International airfreight forwarders are faced with the problem of consolidating shipments for effcient transportation by airline carriers. The use of standard unit loading devices (ULDs) is a solution adopted by the airfreight industry to speed up cargo loading, increase safety, and protect cargo. We study the airfreight consolidation problem from the forwarders perspective where a decision on the number of ULDs used and the assignment of shipments to ULDs is optimized. The cost of using a ULD consists of a fixed charge and depends on the weight of the cargo it contains.
Jatin Nathwani
Management of Technology
Mark Aagaard - Electrical and Computer Engineering
Bonwoo Koo (Supervisor) - Management Sciences
Brian Cozzarin - Management Sciences
Selcuk Onay - Management Sciences
Margaret Dalziel - CBET
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.
The 2018 Management Engineering Design Symposium was held on Friday, March 16. Eleven teams of 4th year management engineering students showcased their innovative designs. The event was very well attended, with all projects evaluated by a number of professors, graduate students, and management engineering alumni. In addition, projects were also evaluated by all other visitors, who helped select the People's Choice Award.
Accounting for the adverse impact of "non-average" events has become essential in many applications involving decision making under uncertainty. Its implementation through decision models, namely stochastic programs, requires careful measurement of risk that reflects one's concern about uncertain outcomes. Important theories such as convex risk measures outline conditions required for risk measurement but provide little guidance for cases not meeting the conditions. Unfortunately, such cases are more than common in real-life situations.