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Is it possible for QBSolve to return an infeasible solution to the problem, even though matrix Q is guaranteed to be correct?

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I'm modeling a QUBO problem, using D-Wave's QBSolve to return a solution to an original optimization problem P, and I'm aware that matrix Q matches problem P perfectly. I already know that QBSolve doesn't guarantee optimality, but it can return viable solutions. However, I'm coming across infeasible solutions. Is it possible for QBSolve to return an infeasible solution to the problem, even though matrix Q is guaranteed to be correct? If yes, why does this happen? And what are the current alternatives for working with huge matrices that only return viable solutions to the problem? I'm waiting for an answer to my question.

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クアンタム テクノロジー
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Amazon Braket
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AWS-User-1832049
質問済み 2年前264ビュー
1回答
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承認された回答

Hello! QBSolv is now deprecated and it is recommended by D-Wave to use dwave-hybrid.

QBSolv makes uses of the tabu algorithm when running on classical solvers. More information can be found on the docs. Infeasible solutions have not been reported before but I would recommend looking into dwave-hybrid. Let us know if this answers your question!

AWS
Abe C
回答済み 2年前
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エキスパート
Giovanni Lauria
レビュー済み 5日前
  • AWS-User-1832049
    2年前

    Thanks for your response. In light of current dwave-hybrid approaches, I have used the D-wave Simulator for simulated annealing (neal - https://docs.ocean.dwavesys.com/projects/neal/en/latest/reference/sampler.html). Like QBSolv, it is also returning infeasible solutions. In the case of D-wave simulators, are they suitable for large problems, and can they produce unfeasible solutions? I'm sure I'm working with the correct QUBO array for the problem.

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