Investigating QUBO-Compatible Algorithms for Trading and Scheduling Optimization Problems

This project attempts to develop new solution to two problem types that are known to be intractable optimization problems. These include a scheduling problem, the PSP (Project Scheduling Problem), and a problem found in trading (leg-pricing). These problems are investigated to evaluate the applicability of recently developed quantum annealing processors, which specialize in optimization problems, to the examples specific characteristics. These examples are used to explore the suitability of quantum annealing hardware to related problems in scheduling and trading. Interns in this project research, develop, and evaluate methods to translate these problems into the mathematical format required by the hardware – a quadratic unconstrained binary optimization – while addressing the specific constraints of each problem.

Faculty Supervisor:

Laks Lakshmanan;Sathish Gopalakrishnan;Tamon Stephen;Daniel Lee;Mona Berciu;Ramesh Krishnamurti;Ozgur Yilmaz;Douglas Scott;Barry Sanders;Binay Bhattacharya;Leonid Chindelevitch;Mark Schmidt;Roger Melko;Mohamed Hefeeda;Jianping Pan;Isaac Tamblyn;Bruce Shep

Student:

Partner:

1QB Information Technologies Inc;University of Michigan;Georgia Institute of Technology

Discipline:

Computer science

Sector:

Technology; Finance and Insurance; Other; Quantum Science

University:

McGill University; Simon Fraser University; The University of British Columbia; University of Calgary; University of Guelph; University of Ontario Institute of Technology; University of Toronto; University of Victoria; University of Waterloo

Program:

Accelerate