GAPS

Genetic Algorithm Problem Solver

Single-threaded (currently working on concurrency) program to solve problems using genetic algorithm.

Domain

Individual

Represents single solution to a problem with a sequence of 0's and 1's.

Defined with genome length: (Int) and function: (Vector[Boolean] => Double) to compute fitness of the solution.

Public interface contains methods:

1. mutate: (Double => Individual) creates new Individual based on a mutation probability.

2. cross: ((Individual, Double) => (Individual, Individual)) produces pair of children from crossing two Individuals.

GeneticAlgorithm

Defined with population size, crossing probability, mutation probability and a population (generation).

To create GA it is needed to provide fitness function: (Vector[Boolean] => Double) as well (will be changed).

Public interface contains methods:

1. calculateSequentialStatic: (Int => GeneticAlgorithm) calculates given iterations in a single thread without adjusting mutation and crossing probabilities.

2. solution: (String) returns the solution with the highest fitness value of the generation contained in this GeneticAlgorithm object.

Working on implementation of:

1. calculateSequentialDynamic: (Int => GeneticAlgorithm)

2. calculateParallelStatic: (Int => GeneticAlgorithm)

3. calculateParallelDynamic: (Int => GeneticAlgorithm)

Author

• Michal Szturo - Initial work - mstr93

License

Version 1.1, December 2016

Copyright (C) 2018 Michal Szturo

Everyone is permitted to copy and distribute verbatim or modified copies of this license document.

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Acknowledgments

• Phil Sturgeon - Providing a license - philsturgeon

• Stephen McDonald - Providing examples for MergeSort in Akka - stephenmcd