Optimizing heuristics for spin-glass problems for diverse solutions

Optimization problems, such as finding the shortest or fastest path to a destination are ubiquitous in industry. Hower, for some industrial applications it may be desirable to have a set of few diverse, yet nearly optimal solutions. The goal of this project is to create new optimization problem solvers that focus on both quality and diversity of the solutions proposed. These solvers will subsequently be used to assess the performance of the D-Wave quantum annealer processor.

Intern: 
Alex Zucca
Faculty Supervisor: 
Malcolm Kennett
Province: 
British Columbia
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