Kwayoyin Algorithms

Halitta lissafi mai tsauri ne heuristic, stochastic ingantawa hanyoyin cewa an samarwa a karon farko a shekarar 1975, Holland. Suna dogara ne a kan akidar juyin halitta daga zabin yanayi, wanda yayi ko Darwin.

Halitta Algorithms aiki tare da wani iri-iri na mutane, cewa shi ne mai yawan inda kowane mutum zai iya zama a matsayin wani bayani da wani musamman matsalar. Kowane mutum na da da za a kiyasta a kan mataki na karbuwa, dangane da yadda mai kyau ne bayani da ya dace da shi. Idan muka yi la'akari da shi dangane da yanayi, akwai kiyasta mataki na iya aiki na jiki a lokacin gasar domin albarkatu. Mutane ne yafi saba, zai iya haifa ta hanyar giciye-waddan da sauran mambobi na al'ummar jihar. Wannan sa bayyanar da sabon jinsi wanda ya hada wasu halaye daukar kwayar cutar a matsayin gado ne daga iyaye.

Kadan saba mutane za su iya haifa zurriyarsu akwai m iya, don haka da cewa da kaddarorin da suka mallaka, za a hankali bace a lokacin juyin halitta daga cikin daukacin jama'ar. Wani lokaci akwai maras wata-wata canje-canje a genes ko maye gurbi. Sai dai itace cewa da kyau halaye daga tsara zuwa tsara za a rarraba a ko'ina cikin jihar. Interbreeding mutane da cewa su ne mafi kyau dace, abu don abin da aka gudanar da bincike mai search sites cewa wakilci mafi girma a nan gaba. A ƙarshe, shi ne bayani. Halitta Algorithms suna da amfani na da cewa shi ne mai gwada gajeren lokaci m mafita, wanda suke mafi kyau duka. Yana da daraja idan akai la'akari da batun game da shirye-shirye.

Halitta Algorithms an hada da wadannan aka gyara:

- chromosome wakiltar wani bayani da matsala a karkashin shawara kunshi genes. Wannan yawan na chromosomes aka dauke farko.

- wani sa na kalamai (tsara don samar da sabon mafita a kan tushen da sabon yawan).

- haƙiƙa aiki (tsara don kimanta da suitability na mafita).

Domin da kwayoyin algorithm samar da wani misali sa na aiki: selection, maye gurbi da crossover. Yana yiwuwa a yi la'akari da amfani da kwayoyin lissafi mai tsauri da taimakon bayyana abin da kowane musamman sadarwarka. Operator selection ance chromosomes daidai da abin da dabi'u na fitness ayyuka. Ga shi da aka gabatar a kalla biyu daga cikin rare sadarwarka: gasa da caca. caca Hanyar unshi da motsa jiki na selection na mutane da n runs. Ga kowane memba na yawan aiki a cikin caca dabaran ƙunshi daya bangaren ga bukata darajar. Members na yawan tare da wani muhimmanci mafi girma kudi na karbuwa a cikin wannan selection za a zaba mafi sau da yawa fiye da wakilan da suke da low dacewa. Lokacin da hanya ne ya aiwatar da gasar n Teams cewa ba da damar mutane zuwa zaži n. Dalili na kowane taron aza samfurin k abubuwa na yawan jama'ar, da mafi kyau misali daga gare su, ya kamata a zabi.

Idan ka ci gaba da zuwa la'akari da shirye-shirye lissafi mai tsauri, shi wajibi ne ka gaya game da wani Hanyar kira crossbreeding. mararraba sadarwarka da aka yi musayar tsakanin biyu daga rabo na chromosomes ko chromosome a wata alƙarya.

Last sadarwarka - maye gurbi - da stochastic bambancin da chromosome.

Specific shawara na amfani da kwayoyin Algorithms samar da wani karin voluminous abu fiye da zai iya shige a cikin takarda, don haka ya kamata a yi la'akari daban.