Solver Algorithms Options

Tasa d'alternancia del axente

Especifica la probabilidá de qu'un individuu escueya la estratexa d'evolución diferencial.

Suponer variables como non negatives

Mark to force variables to be positive only.

DE: Probabilidá de cruciamientu

Defines the probability of the individual being combined with the globally best point. If crossover is not used, the point is assembled from the own memory of the individual.

DE: Factor d'escala

Demientres el cruciamientu, el factor d'escala decide sobro la «velocidá» del movimientu.

Ciclos de deprendimientu

Defines the number of iterations, the algorithm should take. In each iteration, all individuals make a guess on the best solution and share their knowledge.

PS: Constante cognitiva

Sets the importance of the own memory (in particular the best reached point so far).

PS: Coeficiente de restricción

Defines the speed at which the particles/individuals move towards each other.

PS: Probabilidá de mutación

Defines the probability, that instead of moving a component of the particle towards the best point, it randomly chooses a new value from the valid range for that variable.

PS: Constante social

Sets the importance of the global best point between all particles/individuals.

Show Enhanced Solver Status

If enabled, an additional dialog is shown during the solving process which gives information about the current progress, the level of stagnation, the currently best known solution as well as the possibility, to stop or resume the solver.

Size of Swarm

Defines the number of individuals to participate in the learning process. Each individual finds its own solutions and contributes to the overall knowledge.

Stagnation Limit

If this number of individuals found solutions within a close range, the iteration is stopped and the best of these values is chosen as optimal.

Stagnation Tolerance

Defines in what range solutions are considered “similar”.

Use ACR Comparator

Si ta desactiváu (predeterminao), s'usará el comparador BCH. Esti compara dos individuos mirando primero los saltos de les sos restricciones y, sólo si son iguales, mide la solución actual.

Si ta activáu, s'usará el comparador ACR. Esti compara dos individuos que dependen de la repetición actual y mide la so bondá respeuto a les peores soluciones conocíes de la biblioteca (respeuto a los saltos de les restricciones).

Usar un puntu d'aniciu al debalu

Si ta activáu, la biblioteca se llena simplemente con puntos escoyíos al debalu.

Si ta desactiváu, los valores presentes anguaño (tal como los diera l'usuariu) s'inxerten na biblioteca como puntu de referencia.

Variable Bounds Guessing

If enabled (default), the algorithm tries to find variable bounds by looking at the starting values.

Variable Bounds Threshold

When guessing variable bounds, this threshold specifies, how the initial values are shifted to build the bounds. For an example how these values are calculated, please refer to the Manual in the Wiki.

Suponer variables como non negatives

Mark to force variables to be positive only.

Ciclos de deprendimientu

Defines the number of iterations, the algorithm should take. In each iteration, all individuals make a guess on the best solution and share their knowledge.

Show Enhanced Solver Status

If enabled, an additional dialog is shown during the solving process which gives information about the current progress, the level of stagnation, the currently best known solution as well as the possibility, to stop or resume the solver.

Tamañu de la biblioteca

Defines the amount of information to store in the public library. Each individual stores knowledge there and asks for information.

Size of Swarm

Defines the number of individuals to participate in the learning process. Each individual finds its own solutions and contributes to the overall knowledge.

Stagnation Limit

If this number of individuals found solutions within a close range, the iteration is stopped and the best of these values is chosen as optimal.

Stagnation Tolerance

Defines in what range solutions are considered “similar”.

Use ACR Comparator

Variable Bounds Guessing

If enabled (default), the algorithm tries to find variable bounds by looking at the starting values.

Variable Bounds Threshold

When guessing variable bounds, this threshold specifies, how the initial values are shifted to build the bounds. For an example how these values are calculated, please refer to the Manual in the Wiki.

Suponer variables como enteros

Mark to force variables to be integers only.

Suponer variables como non negatives

Mark to force variables to be positive only.

Epsilon level

Epsilon level. Valid values are in range 0 (very tight) to 3 (very loose). Epsilon is the tolerance for rounding values to zero.

Llímite a fondu de rama-y-obligación

Specifies the maximum branch-and-bound depth. A positive value means that the depth is absolute. A negative value means a relative branch-and-bound depth limit.

Solver time limit

Sets the maximum time for the algorithm to converge to a solution.

Suponer variables como enteros

Mark to force variables to be integers only.

Suponer variables como non negatives

Mark to force variables to be positive only.

Solver time limit

Sets the maximum time for the algorithm to converge to a solution.

Swarm algorithm

Set the swarm algorithm. 0 for differential evolution and 1 for particle swarm optimization. Default is 0.