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Source code for qiskit_optimization.applications.knapsack

# This code is part of Qiskit.
#
# (C) Copyright IBM 2018, 2021.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any modifications or derivative works of this code must retain this
# copyright notice, and modified files need to carry a notice indicating
# that they have been altered from the originals.

"""An application class for the Knapsack problem"""
from typing import List, Union

import numpy as np
from docplex.mp.model import Model

from qiskit_optimization.algorithms import OptimizationResult
from qiskit_optimization.problems.quadratic_program import QuadraticProgram
from qiskit_optimization.translators import from_docplex_mp
from .optimization_application import OptimizationApplication


[docs]class Knapsack(OptimizationApplication): """Optimization application for the "knapsack problem" [1]. References: [1]: "Knapsack problem", https://en.wikipedia.org/wiki/Knapsack_problem """ def __init__(self, values: List[int], weights: List[int], max_weight: int) -> None: """ Args: values: A list of the values of items weights: A list of the weights of items max_weight: The maximum weight capacity """ self._values = values self._weights = weights self._max_weight = max_weight
[docs] def to_quadratic_program(self) -> QuadraticProgram: """Convert a knapsack problem instance into a :class:`~qiskit_optimization.problems.QuadraticProgram` Returns: The :class:`~qiskit_optimization.problems.QuadraticProgram` created from the knapsack problem instance. """ mdl = Model(name="Knapsack") x = {i: mdl.binary_var(name=f"x_{i}") for i in range(len(self._values))} mdl.maximize(mdl.sum(self._values[i] * x[i] for i in x)) mdl.add_constraint(mdl.sum(self._weights[i] * x[i] for i in x) <= self._max_weight) op = from_docplex_mp(mdl) return op
[docs] def interpret(self, result: Union[OptimizationResult, np.ndarray]) -> List[int]: """Interpret a result as item indices Args: result : The calculated result of the problem Returns: A list of items whose corresponding variable is 1 """ x = self._result_to_x(result) return [i for i, value in enumerate(x) if value]
@property def max_weight(self) -> int: """Getter of max_weight Returns: The maximal weight for the knapsack problem """ return self._max_weight @max_weight.setter def max_weight(self, max_weight: int) -> None: """Setter of max_weight Args: max_weight: The maximal weight for the knapsack problem """ self._max_weight = max_weight

© Copyright 2018, 2021, Qiskit Optimization Development Team.

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