Click here to load reader

Genetic Algorithms Vida Movahedi November 2006. Contents What are Genetic Algorithms? From Biology Evolution To Genetic Algorithms Demo

  • View
    218

  • Download
    1

Embed Size (px)

Text of Genetic Algorithms Vida Movahedi November 2006. Contents What are Genetic Algorithms? From Biology ...

  • Slide 1

Genetic Algorithms Vida Movahedi November 2006 Slide 2 Contents What are Genetic Algorithms? From Biology Evolution To Genetic Algorithms Demo Slide 3 What are Genetic Algorithms? A method of solving Optimization Problems Exponentially large set of solutions Easy to compute cost or value Search algorithm (looking for the optimum) Very similar to random search?! Population- based We start with a set of possible solutions (initial population) and evolve it to get to the optimum Also called Evolutionary Algorithms Based on evolution in biology Slide 4 From Biology Charles Darwin (1859) Natural selection, survival of the fittest Improvement of species Can we use the same idea to get an optimal solution? Slide 5 Evolution To implement optimization as evolution, We need Mapping features to genes, showing each individual with a chromosome An initial population Have a function to measure fitness same as what we want to optimize Implement and apply Reproduction Replace offspring in old generation Have an exit condition for looping over generations Slide 6 Initial Population Representation of possible solutions as chromosomes Binary Real etc. Random initial population If not random stuck in local optima Slide 7 Recombination (crossover) Random crossover points Inheriting genes from one parent Slide 8 Mutation Random Mutation Point Changing gene value to a random value Slide 9 to Genetic Algorithms BEGIN /* genetic algorithm*/ Generate initial population ; Compute fitness of each individual ; LOOP Select individuals from old generations for mating ; Create offspring by applying recombination and/or mutation to the selected individuals ; Compute fitness of the new individuals ; Kill old individuals,insert offspring in new generation ; IF Population has converged THEN exit loop; END LOOP END Slide 10 Simple Example Slide 11 Slide 12 Slide 13 Slide 14 Example http://www.rennard.org/alife/english/gavgb. htmlhttp://www.rennard.org/alife/english/gavgb. html Slide 15 Slide 16 References [1] Hue, Xavier (1997), Genetic Algorithms for Optimisation: Background and Applications, http://www.epcc.ed.ac.uk/overview/publicat ions/training_material/tech_watch/97_tw/te chwatch-ga/ http://www.epcc.ed.ac.uk/overview/publicat ions/training_material/tech_watch/97_tw/te chwatch-ga/ [2] Whitely, Darell (1995), A Genetic Algorithm Tutorial, http://samizdat.mines.edu/ga_tutorial/ http://samizdat.mines.edu/ga_tutorial/ Slide 17 Questions?