Optimization algorithms

qiskit.optimization.algorithms

Algorithms for optimization problems.

Base classes for algorithms and results


`OptimizationAlgorithm`	An abstract class for optimization algorithms in Qiskit’s optimization module.
`MultiStartOptimizer`	An abstract class that implements multi start optimization and should be sub-classed by other optimizers.
`OptimizationResult`	A base class for optimization results.


`ADMMOptimizationResult`	ADMMOptimization Result.
`ADMMOptimizer`	An implementation of the ADMM-based heuristic.
`ADMMParameters`	Defines a set of parameters for ADMM optimizer.
`ADMMState`	Internal computation state of the ADMM implementation.
`CobylaOptimizer`	The SciPy COBYLA optimizer wrapped as an Qiskit `OptimizationAlgorithm`.
`CplexOptimizer`	The CPLEX optimizer wrapped as an Qiskit `OptimizationAlgorithm`.
`GroverOptimizationResult`	A result object for Grover Optimization methods.
`GroverOptimizer`	Uses Grover Adaptive Search (GAS) to find the minimum of a QUBO function.
`IntermediateResult`	Defines whether the intermediate results of `RecursiveMinimumEigenOptimizer` at each iteration should be stored and returned to the end user.
`MinimumEigenOptimizationResult`	Minimum Eigen Optimizer Result.
`MinimumEigenOptimizer`	A wrapper for minimum eigen solvers from Qiskit Aqua.
`OptimizationResultStatus`	Termination status of an optimization algorithm.
`RecursiveMinimumEigenOptimizationResult`	Recursive Eigen Optimizer Result.
`RecursiveMinimumEigenOptimizer`	A meta-algorithm that applies a recursive optimization.
`SlsqpOptimizationResult`	SLSQP optimization result, defines additional properties that may be returned by the optimizer.
`SlsqpOptimizer`	The SciPy SLSQP optimizer wrapped as an Qiskit `OptimizationAlgorithm`.
`SolutionSample`	A sample of an optimization solution

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