Differential
Properties
| Convergence |
Gets the collection of convergence tests for the algorithm.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Crossover | Gets or sets the crossover rate used in the algorithm. |
| Differential | Gets or sets the differential weight factor used in the mutation step. |
| Dimensions |
Gets or sets the number of dimensions of the optimization problem.
(Inherited from PopulationBasedOptimizer<TPopulation, TCandidate>) |
| Dithering | Gets or sets the dithering range used when WeightDithering is set to Uniform. |
| Diversity |
Gets the convergence test that measures population diversity.
(Inherited from PopulationBasedOptimizer<TSolution, TPopulation, TCandidate>) |
| Estimated |
Gets a value indicating the size of the absolute
error of the result.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Evaluations |
Gets the number of evaluations needed to execute the algorithm.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Extremum |
Gets or sets the current best approximation to the extremum.
(Inherited from MultidimensionalOptimizer<T, TReport>) |
| Extremum |
Gets or sets the type of extremum.
(Inherited from MultidimensionalOptimizer<T, TReport>) |
| Has |
Indicates whether the degree of parallelism is a property that is shared
across instances.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Initial |
Gets or sets the initial value for the iteration.
(Inherited from MultidimensionalOptimizer<T, TReport>) |
| Initialization |
Gets or sets the method used to initialize the population.
(Inherited from PopulationBasedOptimizer<TPopulation, TCandidate>) |
| Iterations |
Gets the number of iterations needed by the
algorithm to reach the desired accuracy.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Lower |
Gets or sets the vector of lower bounds for the solution.
(Inherited from PopulationBasedOptimizer<TPopulation, TCandidate>) |
| Max |
Gets or sets the maximum degree of parallelism enabled by this instance.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Max |
Gets or sets the maximum number of evaluations during the calculation.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Max | Gets or sets the maximum number of iterations
to use when approximating the roots of the target
function.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Min |
Gets or sets the minimum iterations that have to be performed.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Mutation | Gets or sets the mutation strategy used to generate trial vectors. |
| Objective |
Gets or sets the objective function.
(Inherited from MultidimensionalOptimizer<T, TReport>) |
| Parallel |
Gets or sets the configuration for the parallel behavior of the algorithm.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Population |
Gets the current population of solutions.
(Inherited from PopulationBasedOptimizer<TSolution, TPopulation, TCandidate>) |
| Population |
Gets the convergence test that uses the population's coefficient of variation.
(Inherited from PopulationBasedOptimizer<TSolution, TPopulation, TCandidate>) |
| Population | Gets or sets the population multiplier used to determine the population size. |
| Population |
Gets or sets the population size used in the algorithm.
(Inherited from PopulationBasedOptimizer<TSolution, TPopulation, TCandidate>) |
| Random |
Gets or sets the random number generator used by the optimizer.
(Inherited from PopulationBasedOptimizer<TSolution, TPopulation, TCandidate>) |
| Result |
Gets the result of an algorithm after it has executed.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Solution |
Gets the result of an algorithm after it has executed.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Stagnation | Gets or sets the stagnation limit, which is the number of iterations without improvement before declaring stagnation. |
| Status |
Gets the AlgorithmStatus following
an execution of the algorithm.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Throw |
Gets or sets whether to throw an
exception when the algorithm fails to converge.
(Inherited from ManagedIterativeAlgorithm<T, TError, TReport>) |
| Upper |
Gets or sets the upper bounds for the solution.
(Inherited from PopulationBasedOptimizer<TPopulation, TCandidate>) |
| Value |
Gets or sets the current value of the objective function.
(Inherited from MultidimensionalOptimizer<T, TReport>) |
| Value |
Gets the SimpleConvergenceTest<T> that uses the value of the target functions.
(Inherited from MultidimensionalOptimizer<T, TReport>) |
| Weight | Gets or sets the type of dithering applied to the differential weight. |