Solving with classical heuristics

Several classical heuristics are made available for solving QUBOs such as tabu search or simulated annealing.

Quickstart: Solving a QUBO with Tabu Search

This tutorial shows how to solve a QUBO problem using the Tabu Search solver.

In [ ]:

from qubosolver import QUBOInstance
from qubosolver.solver import QuboSolver
from qubosolver.config import SolverConfig, ClassicalConfig

qubo = QUBOInstance(coefficients=[[-2.0, 1.0], [1.0, -2.0]])
config = SolverConfig(use_quantum = False, classical=ClassicalConfig(classical_solver_type="tabu_search"))

solver = QuboSolver(qubo, config)

solution = solver.solve()
print(solution)

QUBOSolution(bitstrings=tensor([[1., 1.]]), costs=tensor([-2.]), counts=None, probabilities=None, solution_status=<SolutionStatusType.UNPROCESSED: 'unprocessed'>)

Quickstart: Solving a QUBO with Simulated Annealing

This tutorial shows how to solve a QUBO problem using the Simulated Annealing solver.

In [ ]:

from qubosolver import QUBOInstance
from qubosolver.solver import QuboSolver
from qubosolver.config import SolverConfig

qubo = QUBOInstance(coefficients=[[-2.0, 1.0], [1.0, -2.0]])
config = SolverConfig(use_quantum = False, classical=ClassicalConfig(classical_solver_type="simulated_annealing"))

solver = QuboSolver(qubo, config)

solution = solver.solve()
print(solution)

QUBOSolution(bitstrings=tensor([[1., 1.]]), costs=tensor([-2.]), counts=None, probabilities=None, solution_status=<SolutionStatusType.UNPROCESSED: 'unprocessed'>)