Tsp#
- class Tsp(graph)[ソース]#
ベースクラス:
GraphOptimizationApplication
Optimization application for the 「traveling salesman problem」 [1] based on a NetworkX graph.
参照
[1]: 「Travelling salesman problem」, https://en.wikipedia.org/wiki/Travelling_salesman_problem
- パラメータ:
graph (Graph | ndarray | List) – A graph representing a problem. It can be specified directly as a NetworkX graph, or as an array or list format suitable to build out a NetworkX graph.
Attributes
- graph#
Getter of the graph
- 戻り値:
A graph for a problem
Methods
- static create_random_instance(n, low=0, high=100, seed=None)[ソース]#
Create a random instance of the traveling salesman problem
- draw(result=None, pos=None)#
Draw a graph with the result. When the result is None, draw an original graph without colors.
- パラメータ:
result (OptimizationResult | ndarray | None) – The calculated result for the problem
- static parse_tsplib_format(filename)[ソース]#
Read a graph in TSPLIB format from file and return a Tsp instance.
- パラメータ:
filename (str) – the name of the file.
- 例外:
QiskitOptimizationError – If the type is not 「TSP」
QiskitOptimizationError – If the edge weight type is not 「EUC_2D」
- 戻り値:
A Tsp instance data.
- 戻り値の型:
- static sample_most_likely(state_vector)#
Compute the most likely binary string from state vector.
- パラメータ:
state_vector (QuasiDistribution | Statevector | ndarray | Dict) – state vector or counts or quasi-probabilities.
- 戻り値:
binary string as numpy.ndarray of ints.
- 例外:
ValueError – if state_vector is not QuasiDistribution, Statevector, np.ndarray, or dict.
- 戻り値の型: