Editing Chromosome (evolutionary algorithm) (section)

=== Chromosomes with real-valued or integer genes ===
For the processing of tasks with real-valued or mixed-integer decision variables, EAs such as the [[evolution strategy]]<ref name=":3">{{Cite book |last=Schwefel |first=Hans-Paul |url=https://www.researchgate.net/publication/220690578 |title=Evolution and optimum seeking |date=1995 |publisher=John Wiley & Sons |isbn=0-471-57148-2 |location=New York |oclc=30701094}}</ref> or the real-coded GAs<ref>{{Citation |last1=Eshelman |first1=Larry J. |title=Real-Coded Genetic Algorithms and Interval-Schemata |date=1993 |url=https://linkinghub.elsevier.com/retrieve/pii/B9780080948324500180 |work=Foundations of Genetic Algorithms |volume=2 |pages=187–202 |publisher=Elsevier |language=en |doi=10.1016/b978-0-08-094832-4.50018-0 |isbn=978-0-08-094832-4 |access-date=2023-01-26 |last2=Schaffer |first2=J. David|url-access=subscription }}</ref><ref>{{Cite book |last=Michalewicz |first=Zbigniew |url= |title=Genetic Algorithms + Data Structures = Evolution Programs |date=1996 |publisher=Springer |others=Third, revised and extended edition |isbn=978-3-662-03315-9 |edition= |location=Berlin, Heidelberg |language=en |oclc=851375253}}</ref><ref>{{Cite journal |last1=Deep |first1=Kusum |last2=Singh |first2=Krishna Pratap |last3=Kansal |first3=M.L. |last4=Mohan |first4=C. |date=June 2009 |title=A real coded genetic algorithm for solving integer and mixed integer optimization problems |url=https://linkinghub.elsevier.com/retrieve/pii/S0096300309001830 |journal=Applied Mathematics and Computation |language=en |volume=212 |issue=2 |pages=505–518 |doi=10.1016/j.amc.2009.02.044|url-access=subscription }}</ref> are suited. In the case of mixed-integer values, rounding is often used, but this represents some violation of the [[Genetic representation#Relationships between search space and problem space|redundancy requirement]]. If the necessary precisions of the real values can be reasonably narrowed down, this violation can be remedied by using integer-coded GAs.<ref>{{Citation |last1=Wang |first1=Fuchang |title=Decimal-Integer-Coded Genetic Algorithm for Trimmed Estimator of the Multiple Linear Errors in Variables Model |date=2011 |url=http://link.springer.com/10.1007/978-3-642-25255-6_46 |work=Information Computing and Applications |pages=359–366 |editor-last=Liu |editor-first=Baoxiang |series=LNCS 7030 |place=Berlin, Heidelberg |publisher=Springer |doi=10.1007/978-3-642-25255-6_46 |isbn=978-3-642-25254-9 |access-date=2023-01-23 |last2=Cao |first2=Huirong |last3=Qian |first3=Xiaoshi |editor2-last=Chai |editor2-first=Chunlai|url-access=subscription }}</ref><ref>{{Cite journal |last1=Cheng |first1=Xueli |last2=An |first2=Linchao |last3=Zhang |first3=Zhenhua |date=2019 |title=Integer Encoding Genetic Algorithm for Optimizing Redundancy Allocation of Series-parallel Systems |journal=Journal of Engineering Science and Technology Review |volume=12 |issue=1 |pages=126–136|doi=10.25103/JESTR.121.15 |s2cid=149497992 |doi-access=free }}</ref> For this purpose, the valid digits of real values are mapped to integers by multiplication with a suitable factor. For example, 12.380 becomes the integer 12380 by multiplying by 1000. This must of course be taken into account in genotype-phenotype mapping for evaluation and result presentation. A common form is a chromosome consisting of a list or an array of integer or real values.