Chromosome (evolutionary algorithm): Difference between revisions

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==Chromosome design==

The design of the chromosome and its parameters is by necessity specific to the problem to be solved. Traditionally, chromosomes are represented in binary as strings of 0s and 1s, however other encodings are also possible;<ref name=ga-tutorial>{{cite journal|last1=Whitley|first1=Darrell|title=A genetic algorithm tutorial|journal=Statistics and Computing|date=June 1994|volume=4|issue=2|doi=10.1007/BF00175354}}<!--|accessdate=12 August 2015}}--></ref> almost any representation which allows the solution to be represented as a finite-length string can be used.<ref name=what-are-gas>{{cite web|title=What are Genetic Algorithms?|url=http://www.optiwater.com/optiga/ga.html|accessdate=12 August 2015}}</ref> Finding a suitable representation of the problem ___domain for a chromosome is an important consideration, as a good representation will make the search easier by limiting the search space; similarly, a poorer representation will allow a larger search space.<ref name=ga-notes>{{cite web|title=Genetic algorithms|url=http://www.cse.unsw.edu.au/~billw/cs9414/notes/ml/05ga/05ga.html|accessdate=12 August 2015}}</ref> The [[mutation (genetic algorithm)|mutation]] [[genetic operator|operator]] and [[crossover (genetic algorithm)|crossover]] operator employed by the genetic algorithm must also take into account the chromosome's design.

===Example 1: binary representation===