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Can QAOA solve a constraint binary optimization problem? QAOA is short for Quantum Approximate Optimization Algorithm. I read the information https://qiskit.org/textbook/ch-applications/qaoa.html.

But I'm not sure whether it can solve a constraint binary optimization problem.

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It can actually and this is done by adding penalties to include the constraints in the cost function. See this article on formulations of different problems.

There also exist an adaptation for constrained problems. See this articla on the Quantum Alternating Operator Ansatz.

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  • $\begingroup$ Thanks. I will read the two papers you recommend. It will take me time to finish reading it as I just begin quantum computing. Can you give me a Qiskit code to solve a constrained binary optimization with QAOA. Many thanks. $\endgroup$
    – user14153
    Dec 18, 2020 at 5:45
  • $\begingroup$ I could not find any for Qiskit in their githubs. Only this notebook shows the TSP formulation you could use to run QAOA on (for cost hamiltonian): github.com/Qiskit/qiskit-tutorials/blob/master/tutorials/… . Maybe worth for yourself to try QAOA on? $\endgroup$
    – cnada
    Dec 18, 2020 at 9:32
  • $\begingroup$ Yes, QAOA can solve a constraint mix integer programming. $\endgroup$
    – user14153
    Dec 21, 2020 at 17:46

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