MCScheduling 1.0
Set of Algorithms for Solving Mixed-Criticality Scheduling
Public Member Functions
MCScheduling.GeneticAlgorithm.CSigmaScaling Class Reference

Sigma scaling may be used to force a constant selection pressure over many generations. More...

Inheritance diagram for MCScheduling.GeneticAlgorithm.CSigmaScaling:
MCScheduling.GeneticAlgorithm.IFitnessScaler

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Public Member Functions

void scale (CPopulation population)
 Scales the fitness scores of the individuals within the specified population.

Detailed Description

Sigma scaling may be used to force a constant selection pressure over many generations.

It works like this: First, the average fitness score - averageFitness - is calculated, and then the standard deviation of the fitness scores - sigma - is calculated. Eventually a new fitness score for each individual in the specified population is assigned according to this equation: newFitnessScore = (oldFitnessScore - averageFitness) / (2 * sigma) If the sigma is 0, then all the fitness scores are set to 1.0.


Member Function Documentation

void MCScheduling.GeneticAlgorithm.CSigmaScaling.scale ( CPopulation  population)

Scales the fitness scores of the individuals within the specified population.

For more information look at the description of the CSigmaScaling class.

Parameters:
populationThe population of individuals to be scaled.

Implements MCScheduling.GeneticAlgorithm.IFitnessScaler.

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