Quantum computing-enhanced systems and methods for large-scale constrained optimization

A method comprising:

• identifying an optimization problem;
• decomposing the identified optimization problem into two or more sub-problems, each of the two or more sub-problems being associated with a disjoint subset of a plurality of variables;
• performing two or more iterations of (i) executing a first algorithm for a first one of the two or more sub-problems with a first subset of the plurality of variables on a classical computing device comprising a classical processor and (ii) executing a second algorithm for a second one of the two or more sub-problems with a second subset of the plurality of variables on a quantum computing device comprising a quantum processor;
• and
• determining a solution for the optimization problem based at least in part on results of execution of the first algorithm and the second algorithm in at least one of the two or more iterations;
• wherein, in each of at least a first subset of the two or more iterations, execution of the first algorithm for the first sub-problem on the classical computing device is based at least in part on at least one result from a previously completed one of the two or more iterations of execution of the second algorithm for the second sub-problem on the quantum computing device;
• and
• wherein, in each of at least a second subset of the two or more iterations, execution of the second algorithm for the second sub-problem on the quantum computing device is based at least in part on at least one result from a previously completed one of the two or more iterations of execution of the first algorithm for the first sub-problem on the classical computing device;
• and
• wherein the method is performed by at least one processing device comprising a processor coupled to a memory.

A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code, when executed by at least one processing device comprising a processor coupled to a memory, causes the at least one processing device:

• to identify an optimization problem;
• to decompose the identified optimization problem into two or more sub-problems, each of the two or more sub-problems being associated with a disjoint subset of a plurality of variables;
• to perform two or more iterations of (i) executing a first algorithm for a first one of the two or more sub-problems with a first subset of the plurality of variables on a classical computing device comprising a classical processor and (ii) executing a second algorithm for a second one of the two or more sub-problems with a second subset of the plurality of variables on a quantum computing device comprising a quantum processor;
• and
• to determine a solution for the optimization problem based at least in part on results of execution of the first algorithm and the second algorithm in at least one of the two or more iterations;
• wherein, in each of at least a first subset of the two or more iterations, execution of the first algorithm for the first sub-problem on the classical computing device is based at least in part on at least one result from a previously completed one of the two or more iterations of execution of the second algorithm for the second sub-problem on the quantum computing device;
• and
• wherein, in each of at least a second subset of the two or more iterations, execution of the second algorithm for the second sub-problem on the quantum computing device is based at least in part on at least one result from a previously completed one of the two or more iterations of execution of the first algorithm for the first sub-problem on the classical computing device.