Tabu Search

`TabuSearchSolver`

Classical solver using Tabu Search. Designed to integrate with the solver factory.

Signature

class TabuSearchSolver(BaseClassicalSolver):
    def solve(self) -> QUBOSolution

Description

This solver applies a Tabu Search metaheuristic to escape local minima and explore the solution space. It is suitable for solving QUBO instances classically without relying on quantum hardware. The implementation is based on TabuSearchSolver from the Ocean SDK, and returns solutions compatible with the QUBOSolution interface used across the qubo-solver package.

Fields

Field	Type	Description
`use_quantum`	`bool`	Have to be `False` to use a classical solver.
`classical_solver_type`	`str`	Set to `"tabu_search"` to use Tabu Search as the solving method.
`tabu_x0`	`torch.Tensor`	`None`
`tabu_tenure`	`int`	Number of iterations a move (bit flip) remains tabu.
`tabu_max_no_improve`	`int`	Maximum number of consecutive iterations without improvement before termination.
`tabu_time_limit`	`float`	Maximum execution time for Tabu Search, in seconds. If infinite, no time limit is applied.

Usage

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", tabu_time_limit=300.0))

solver = QuboSolver(qubo, config)

solution = solver.solve()
print(solution)

QUBOSolution(bitstrings=tensor([[0, 1]], dtype=torch.int32), costs=tensor([-2.]), counts=tensor([1]), probabilities=tensor([1.]), solution_status=)

Notes

Recommended for classical heuristics when reproducibility and control over local search dynamics are desired.