mgo/mgo.evolution.algorithm

mgo.evolution.algorithm

package mgo.evolution.algorithm

Type members

Classlikes

object CDGenome
object EMPPSE
Companion
class
case
class EMPPSE(lambda: Int, phenotype: Vector[Double] => Vector[Double], pattern: Vector[Double] => Vector[Int], continuous: Vector[C], reject: Option[Vector[Double] => Boolean], iterations: Int, tolerance: Double, warmupSampler: Int, dilation: Double, fitOnRarest: Int)
Companion
object
object EMPPSEOperation
case
class EvolutionState[S](generation: Long, evaluated: Long, startTime: Long, s: S)
object GenomeVectorDouble
object NSGA2
Companion
class
case
class NSGA2(mu: Int, lambda: Int, fitness: (Vector[Double], Vector[Int]) => Vector[Double], continuous: Vector[C], discrete: Vector[D], operatorExploration: Double, reject: Option[(Vector[Double], Vector[Int]) => Boolean])
Companion
object
object NSGA2Operations
object NSGA3

NSGA-III algorithm for many-objective problems

NSGA-III algorithm for many-objective problems

Deb, K., & Jain, H. (2013). An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints. IEEE transactions on evolutionary computation, 18(4), 577-601.

For U-NSGA-III, see Seada, H., & Deb, K. (2015, March). U-NSGA-III: a unified evolutionary optimization procedure for single, multiple, and many objectives: proof-of-principle results. In International conference on evolutionary multi-criterion optimization (pp. 34-49). Springer, Cham.

Companion
class
case
class NSGA3(popSize: Int, referencePoints: ReferencePoints, fitness: (Vector[Double], Vector[Int]) => Vector[Double], continuous: Vector[C], discrete: Vector[D], operatorExploration: Double, reject: Option[(Vector[Double], Vector[Int]) => Boolean])
Companion
object
object NSGA3Operations
object NoisyNSGA2
Companion
class
case
class NoisyNSGA2[P](mu: Int, lambda: Int, fitness: (Random, Vector[Double], Vector[Int]) => P, aggregation: Vector[P] => Vector[Double], continuous: Vector[C], discrete: Vector[D], historySize: Int, cloneProbability: Double, operatorExploration: Double, reject: Option[(Vector[Double], Vector[Int]) => Boolean])
Companion
object
object NoisyNSGA2Operations
object NoisyNSGA3
Companion
class
case
class NoisyNSGA3[P](popSize: Int, referencePoints: ReferencePoints, fitness: (Random, Vector[Double], Vector[Int]) => P, aggregation: Vector[P] => Vector[Double], continuous: Vector[C], discrete: Vector[D], historySize: Int, cloneProbability: Double, operatorExploration: Double, reject: Option[(Vector[Double], Vector[Int]) => Boolean])
Companion
object
object NoisyNSGA3Operations
object NoisyOSE
Companion
class
case
class NoisyOSE[P](mu: Int, lambda: Int, fitness: (Random, Vector[Double], Vector[Int]) => P, limit: Vector[Double], origin: (Vector[Double], Vector[Int]) => Vector[Int], aggregation: Vector[P] => Vector[Double], continuous: Vector[C], discrete: Vector[D], historySize: Int, cloneProbability: Double, operatorExploration: Double, reject: Option[(Vector[Double], Vector[Int]) => Boolean])
Companion
object
object NoisyOSEOperations
object NoisyPSE
Companion
class
case
class NoisyPSE[P](lambda: Int, phenotype: (Random, Vector[Double], Vector[Int]) => P, pattern: Vector[Double] => Vector[Int], aggregation: Vector[P] => Vector[Double], continuous: Vector[C], discrete: Vector[D], historySize: Int, cloneProbability: Double, operatorExploration: Double, reject: Option[(Vector[Double], Vector[Int]) => Boolean])
Companion
object
object NoisyPSEOperations
object NoisyProfile
Companion
class
case
class NoisyProfile[N, P](muByNiche: Int, lambda: Int, fitness: (Random, Vector[Double], Vector[Int]) => P, aggregation: Vector[P] => Vector[Double], niche: Individual[P] => N, continuous: Vector[C], discrete: Vector[D], historySize: Int, cloneProbability: Double, operatorExploration: Double, reject: Option[(Vector[Double], Vector[Int]) => Boolean])
Companion
object
object NoisyProfileOperations
object OSE
Companion
class
case
class OSE(mu: Int, lambda: Int, fitness: (Vector[Double], Vector[Int]) => Vector[Double], limit: Vector[Double], origin: (Vector[Double], Vector[Int]) => Vector[Int], continuous: Vector[C], discrete: Vector[D], operatorExploration: Double, reject: Option[(Vector[Double], Vector[Int]) => Boolean])
Companion
object
object OSEOperation
object PSE
Companion
class
case
class PSE(lambda: Int, phenotype: (Vector[Double], Vector[Int]) => Vector[Double], pattern: Vector[Double] => Vector[Int], continuous: Vector[C], discrete: Vector[D], operatorExploration: Double, reject: Option[(Vector[Double], Vector[Int]) => Boolean])
Companion
object
object PSEOperations
object Profile
Companion
class
case
class Profile[N](lambda: Int, fitness: (Vector[Double], Vector[Int]) => Vector[Double], continuous: Vector[C], discrete: Vector[D], niche: Individual[Vector[Double]] => N, nicheSize: Int, operatorExploration: Double, reject: Option[(Vector[Double], Vector[Int]) => Boolean])
Companion
object
object ProfileOperations
object deterministic
object noisy

Types

type Archive[I] = Array[I]
type HitMap = Map[Vector[Int], Int]
type HitMapState = Map[Vector[Int], Int]

Value members

Concrete methods

def averageAggregation(history: Vector[Vector[Double]]): Vector[Double]
def drawOperator[O](opsAndWeights: Vector[(O, Double)], exploration: Double, rng: Random): (O, Int)
def operatorProportions[I](operation: I => Option[Int], is: Vector[I]): Map[Int, Double]
def randomTake[G](gs: Vector[G], lambda: Int, random: Random): Vector[G]
def scaleContinuousValues(values: Vector[Double], genomeComponents: Vector[C]): Vector[Double]
def selectOperator[S, G](operators: Vector[(S, G, Random) => G], opStats: Map[Int, Double], exploration: Double): (S, G, Random) => (G, Int)