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Genetic Algorithms
Vida Movahedi
November 2006
Contents
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What are Genetic Algorithms?
From Biology …
Evolution
… To Genetic Algorithms
Demo
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
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?
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
Initial Population
• Representation of possible solutions as
chromosomes
– Binary
– Real
– etc.
• Random initial population
• If not random  stuck in local optima
Recombination (crossover)
• Random crossover points
• Inheriting genes from one parent
Mutation
• Random Mutation Point
• Changing gene value to a random value
… 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
Simple Example
Example
• http://www.rennard.org/alife/english/gavgb.
html
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/
• [2] Whitely, Darell (1995), “A Genetic
Algorithm Tutorial”,
http://samizdat.mines.edu/ga_tutorial/
Questions?