Editing Evolutionary algorithm (section)

==Generic definition==

The following is an example of a generic evolutionary algorithm:<ref>{{cite book |last1=Jansen |first1=Thomas |last2=Weyland |first2=Dennis |chapter=Analysis of evolutionary algorithms for the longest common subsequence problem |title=Proceedings of the 9th annual conference on Genetic and evolutionary computation |date=7 July 2007 |pages=939–946 |doi=10.1145/1276958.1277148 |chapter-url=https://dl.acm.org/doi/abs/10.1145/1276958.1277148 |publisher=Association for Computing Machinery|isbn=978-1-59593-697-4 }}</ref><ref>{{cite book |last1=Jin |first1=Yaochu |chapter=Evolutionary Algorithms |title=Advanced Fuzzy Systems Design and Applications |series=Studies in Fuzziness and Soft Computing |date=2003 |volume=112 |pages=49–71 |doi=10.1007/978-3-7908-1771-3_2 |chapter-url=https://link.springer.com/chapter/10.1007/978-3-7908-1771-3_2 |publisher=Physica-Verlag HD |isbn=978-3-7908-2520-6 |language=en}}</ref><ref>{{cite book |last1=Tavares |first1=Jorge |last2=Machado |first2=Penousal |last3=Cardoso |first3=Amílcar |last4=Pereira |first4=Francisco B. |last5=Costa |first5=Ernesto |chapter=On the Evolution of Evolutionary Algorithms |title=Genetic Programming |series=Lecture Notes in Computer Science |date=2004 |volume=3003 |pages=389–398 |doi=10.1007/978-3-540-24650-3_37 |chapter-url=https://link.springer.com/chapter/10.1007/978-3-540-24650-3_37 |publisher=Springer |isbn=978-3-540-21346-8 |language=en}}</ref>

# Randomly generate the initial [[population model (evolutionary algorithm)|population]] of [[Chromosome (evolutionary algorithm)|individual]]s, the first generation.
# Evaluate the [[Fitness function|fitness]] of each individual in the population.
# Check, if the goal is reached and the algorithm can be terminated.
# [[Selection (evolutionary algorithm)|Select]] individuals as parents, preferably of higher fitness.
# Produce offspring with optional [[crossover (evolutionary algorithm)|crossover]] (mimicking [[reproduce|reproduction]]).
# Apply [[mutation (evolutionary algorithm)|mutation]] operations on the [[offspring]].
# [[Selection (evolutionary algorithm)|Select]] individuals preferably of lower fitness for replacement with new individuals (mimicking [[natural selection]]).
# Return to 2