1. This site uses cookies. By continuing to use this site, you are agreeing to our use of cookies. Learn More.
  2. Donation with Paypal!!!

    Go to your paypal account and send directly donation to [email protected]

    1 month - 10 $ - Standart VIP

    6 months - 20 $- Standart VIP

    1 year - 30 $- Standart VIP

    2 years - 50 $- Standart VIP

    Gold member for life - 150 $- Standart VIP

    High Vip (Standart VIP include) group please send PM or email to [email protected] for info

    After Donation please send email to [email protected]

  3. Donation Ways 2020


    Paysend
  4. Telegram
Dismiss Notice

Donation with Paypal!!!

Go to your paypal account and send directly donation to [email protected]

1 month - 10 $ - Standart VIP

6 months - 20 $- Standart VIP

1 year - 30 $- Standart VIP

2 years - 50 $- Standart VIP

Gold member for life - 150 $- Standart VIP

High Vip (Standart VIP include) group please send PM or email to [email protected] for info

After Donation please send email to [email protected]

Dismiss Notice
For open hidden message no need write thanks, thank etc. Enough is click to like button on right side of thread.

Genetic Algorithms Component Library

Discussion in 'Delphi Components,Freeware, Open Source' started by AdminDF, Feb 19, 2014.

  1. AdminDF
    Online

    AdminDFAdminDF is a Verified Member Delphifan Staff Member DF Staff

    The Genetic Algorithms Component Library (GACL) is a powerful genetic algorithms solution for Delphi Win32, Win64, OSX, iOS and now Android!   Designed for Delphi 2010-XE5 (Win32/Win64/OSX/iOS/Android), the GACL provides simple yet powerful components for designing, evolving, and using genetic algorithms.

    Genetic algorithms are computer science techniques that seek to solve optimization or search problems. They are inspired by evolutionary biology and approach the search problem as a task of evolving a group or population of candidate individuals through successive generations, selecting fitter (or better) child individuals for each generation, until a solution is found. It uses evolutionary biology techniques such as inheritance, mutation, selection, and crossover (also called recombination).

    [​IMG]

    Download Here
     
    aes7 likes this.

Share This Page