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McMaster University

Project Leader(s): 

Dr. Matt Davison, University of Western Ontario

Project team: 
Dr. Robert Elliott, University of Calgary
Dr. Marcos Escobar Anel, Ryerson University
Dr. Matheus Grasselli, McMaster University
Dr. Tom Hurd, McMaster University
Dr. Rogemar S. Mamon, University of Western Ontario
Dr. Adam Metzler, University of Western Ontario
Dr. Mark Reesor, University of Western Ontario
Dr. Anatoly Swishchuk, University of Calgary
Dr. Tony Ware, University of Calgary
Dr. Traian Pirvu, MacMaster University
Dr. Ivar Ekeland , University of British Columbia
Dr. Rachel Kuske, University of British Columbia
Funding period: 
February 25, 2022 - March 31, 2021

Traders in both financial markets and commodity markets must make educated decisions about when to trade and at what price; this project develops tools to assist with this decision-making process. Working with energy companies, financial software companies as well as companies from the banking and insurance sectors, the research team develops optimal portfolio methods that produce both the best investment decisions and the best hedging strategies for claims in general markets.

Tags: 
Project Leader(s): 

Dr. Anthony Vannelli, University of Guelph & Dr. Miguel F, AnjosEcole Polytechnique

Project team: 
Dr. Abdo Youssef Alfakih, University of Windsor
Dr. Kankar Bhattacharya, University of Waterloo
Dr. Claudio A. Canizares, University of Waterloo
Dr. Richard J. Caron, University of Windsor
Dr. Thomas Coleman, University of Waterloo
Dr. Tim N. Davidson, McMaster University
Dr. Antoine Deza, McMaster University
Dr. Samir Elhedhli, University of Waterloo
Dr. David Fuller, University of Waterloo
Dr. Elizabeth Jewkes, University of Waterloo
Dr. Paul McNicholas, University of Guelph
Dr. Chitra Rangan, University of Windsor
Dr. Tamás Terlaky, Lehigh University
Dr. Stephen Vavasis, University of Waterloo
Dr. Henry Wolkowicz, University of Waterloo
Dr. Guoqing Zhang, University of Windsor
Funding period: 
April 1, 2021 - March 31, 2021

Due to the explosive growth in the technology for manufacturing integrated circuits, modern chips contain millions of transistors. Using sophisticated optimization algorithms, it is possible to achieve notable increases in the performance of the chips, reduce the manufacturing costs, and produce faster, cheaper computing for society. Thus, the objective of this project is to enhance the solution of large-scale optimization problems arising in these applications.