Editing Genetic operator (section)

===Mutation===
{{main|Mutation (evolutionary algorithm)}}
The mutation operator encourages genetic diversity amongst solutions and attempts to prevent the evolutionary algorithm converging to a [[local minimum]] by stopping the solutions becoming too close to one another. In mutating the current pool of solutions, a given solution may change between slightly and entirely from the previous solution.<ref name=":3">{{Cite book |last1=Bäck |first1=Thomas |url=https://www.worldcat.org/oclc/45730387 |title=Evolutionary computation Vol. 1, Basic algorithms and operators |last2=Fogel |first2=David B. |last3=Whitley |first3=Darrell |last4=Angeline |first4=Peter J. |publisher=CRC Press |year=1999 |isbn=0-585-30560-9 |editor-last=Bäck |editor-first=Thomas |location=Boca Racon |pages=237–255 |language=en |chapter=Mutation operators |oclc=45730387 |editor-last2=Fogel |editor-first2=David B. |editor-last3=Michalewicz |editor-first3=Zbigniew}}</ref> By mutating the solutions, an evolutionary algorithm can reach an improved solution solely through the mutation operator.<ref name=ga-intro /> Again, different methods of mutation may be used; these range from a simple ''bit mutation'' (flipping random bits in a binary string chromosome with some low probability) to more complex mutation methods in which genes in the solution are changed, for example by adding a random value from the [[Gaussian distribution]] to the current gene value. As with the crossover operator, the mutation method is usually chosen to match the representation of the solution within the chromosome.<ref name=":3" /><ref name=":0">{{Cite book |last1=Eiben |first1=A.E. |url=http://link.springer.com/10.1007/978-3-662-44874-8 |title=Introduction to Evolutionary Computing |last2=Smith |first2=J.E. |date=2015 |publisher=Springer |isbn=978-3-662-44873-1 |series=Natural Computing Series |location=Berlin, Heidelberg |pages=49–78 |chapter=Representation, Mutation, and Recombination |doi=10.1007/978-3-662-44874-8|s2cid=20912932 }}</ref>