optimisers

Documentation

Index

• type Moead
  • func NewMoead(cmop types.Cmop, chm types.CHM, ...) *Moead
  • func (m Moead) Archive() []types.Individual
  • func (m Moead) CHM() types.CHM
  • func (m Moead) ConstraintViolation() []float64
  • func (m *Moead) Evolve(stage types.Stage)
  • func (m Moead) FeasibleRatio() float64
  • func (m Moead) FunctionEvaluations() int
  • func (m Moead) Generation() int
  • func (m Moead) Ideal() []float64
  • func (m *Moead) Initialise()
  • func (m Moead) MaxFuncEvals() int
  • func (m Moead) MaxViolation() float64
  • func (m Moead) Population() []types.Individual
  • func (m *Moead) Reset()
• type MoeadIndividual
  • func (i MoeadIndividual) Copy() types.Individual
  • func (i MoeadIndividual) D() int
  • func (i MoeadIndividual) Fitness() types.Fitness
  • func (i MoeadIndividual) Genotype() types.Genotype
  • func (i *MoeadIndividual) Initialise()
  • func (i *MoeadIndividual) PolynomialMutation(m float64)
  • func (ind *MoeadIndividual) Repair()
  • func (i *MoeadIndividual) SetFitness(f types.Fitness)
  • func (i *MoeadIndividual) SetGenotype(g []float64)
  • func (i *MoeadIndividual) UpdateFitness() types.Fitness

Types

type Moead

type Moead struct {
	T, WeightDistribution int
	DecisionVariables, Nr int

	F, Cr, DistributionIndex float64
	Weights                  []arrays.Vector
	WeightNeigbourhood       [][]int
	// contains filtered or unexported fields
}

Moead is the struct describing the MOEA/D algorithm.

func NewMoead

func NewMoead(cmop types.Cmop, chm types.CHM, t, weightDistribution, decisionVariables, nr int, f, cr, distributionIndex float64, maxFuncEvals int) *Moead

func (Moead) Archive

func (m Moead) Archive() []types.Individual

func (Moead) CHM

func (m Moead) CHM() types.CHM

func (Moead) ConstraintViolation

func (m Moead) ConstraintViolation() []float64

ConstraintViolation returns the total constraint violation of the population

func (*Moead) Evolve

func (m *Moead) Evolve(stage types.Stage)

Evolve performs the genetic operator on all individuals in the population Based on the stage parameter different evolutionary steps are taken

func (Moead) FeasibleRatio

func (m Moead) FeasibleRatio() float64

FeasibleRatio returns the ratio of feasible feasible individuals in the population

func (Moead) FunctionEvaluations

func (m Moead) FunctionEvaluations() int

FunctionEvaluations returns the current number of function evaluations performed

func (Moead) Generation

func (m Moead) Generation() int

func (Moead) Ideal

func (m Moead) Ideal() []float64

func (*Moead) Initialise

func (m *Moead) Initialise()

Initialise initialises the MOEA/D by calculating the weights, weight neighbourhood, population and ideal point.

func (Moead) MaxFuncEvals

func (m Moead) MaxFuncEvals() int

func (Moead) MaxViolation

func (m Moead) MaxViolation() float64

func (Moead) Population

func (m Moead) Population() []types.Individual

func (*Moead) Reset

func (m *Moead) Reset()

type MoeadIndividual

type MoeadIndividual struct {
	Cmop types.Cmop
	// contains filtered or unexported fields
}

MoeadIndividual is a struct containing information about an individual in the population of an evolutionary algorithm.

func (MoeadIndividual) Copy

func (i MoeadIndividual) Copy() types.Individual

func (MoeadIndividual) D

func (i MoeadIndividual) D() int

func (MoeadIndividual) Fitness

func (i MoeadIndividual) Fitness() types.Fitness

Fitness returnes the fitness value of the individual if it has been calculated

func (MoeadIndividual) Genotype

func (i MoeadIndividual) Genotype() types.Genotype

Genotype returns the genotype of the individual

func (*MoeadIndividual) Initialise

func (i *MoeadIndividual) Initialise()

Initialise initialises the individuals genotype with random floats in the range [0,1]

func (*MoeadIndividual) PolynomialMutation

func (i *MoeadIndividual) PolynomialMutation(m float64)

PolynomialMutation performs the mutation described in the paper https://reader.elsevier.com/reader/sd/pii/S0045782599003898 PPS describes a mutation probability of 1/n where n => length of genotype. We don't iterate but make a 1/n dice roll to check if we're mutating a single alele.

func (*MoeadIndividual) Repair

func (ind *MoeadIndividual) Repair()

func (*MoeadIndividual) SetFitness

func (i *MoeadIndividual) SetFitness(f types.Fitness)

func (*MoeadIndividual) SetGenotype

func (i *MoeadIndividual) SetGenotype(g []float64)

func (*MoeadIndividual) UpdateFitness

func (i *MoeadIndividual) UpdateFitness() types.Fitness

UpdateFitness updates the fitness value of an individual