# qiskit.aqua.algorithms.ClassicalCPLEX¶

class ClassicalCPLEX(operator, timelimit=600, thread=1, display=2)[source]

The Classical CPLEX algorithm (classical).

This algorithm uses the IBM ILOG CPLEX Optimization Studio along with its separately installed Python API to solve optimization problems modeled as an Ising Hamiltonian.

See these installation instructions if you need more information in that regard.

Parameters
• operator (WeightedPauliOperator) – The Ising Hamiltonian as an Operator

• timelimit (int) – A time limit in seconds for the execution

• thread (int) – The number of threads that CPLEX uses. Setting this 0 lets CPLEX decide the number of threads to allocate, but this may not be ideal for small problems for which the default of 1 is more suitable.

• display (int) – Decides what CPLEX reports to the screen and records in a log during mixed integer optimization. This value must be between 0 and 5 where the amount of information displayed increases with increasing values of this parameter.

__init__(operator, timelimit=600, thread=1, display=2)[source]
Parameters
• operator (WeightedPauliOperator) – The Ising Hamiltonian as an Operator

• timelimit (int) – A time limit in seconds for the execution

• thread (int) – The number of threads that CPLEX uses. Setting this 0 lets CPLEX decide the number of threads to allocate, but this may not be ideal for small problems for which the default of 1 is more suitable.

• display (int) – Decides what CPLEX reports to the screen and records in a log during mixed integer optimization. This value must be between 0 and 5 where the amount of information displayed increases with increasing values of this parameter.

Methods

 __init__(operator[, timelimit, thread, display]) type operator WeightedPauliOperator Execute the classical algorithm.

Attributes

 random Return a numpy random. solution return solution
property random

Return a numpy random.

run()

Execute the classical algorithm.

Returns

results of an algorithm.

Return type

dict

property solution

return solution