Solving constrained quadratic binary problems via quantum adiabatic evolution
classification
🧮 math.OC
cs.ETquant-ph
keywords
problemsadiabaticbinaryconstrainedconstraintsquadraticquantumevolution
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Quantum adiabatic evolution is perceived as useful for binary quadratic programming problems that are a priori unconstrained. For constrained problems, it is a common practice to relax linear equality constraints as penalty terms in the objective function. However, there has not yet been proposed a method for efficiently dealing with inequality constraints using the quantum adiabatic approach. In this paper, we give a method for solving the Lagrangian dual of a binary quadratic programming (BQP) problem in the presence of inequality constraints and employ this procedure within a branch-and-bound framework for constrained BQP (CBQP) problems.
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