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TurboGA: A Simple Genetic Algorithm With a Powerful Performance Enhancing Tweak

version (4.27 KB) by Keki Burjorjee
A simple genetic algorithm with a tweak, called clamping, that should improve performance


Updated 17 Dec 2010

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TurboGA is an augmented version of the Matlab script SpeedyGA (also available on File Exchange). TurboGA uses a simple mechanism called clamping, which, according to a new theory about the workings of genetic algorithms (see ), should significantly improve the quality of the solutions returned, especially on large problems.

One of the most effective ways to test this new theory is by studying the efficacy of clamping on a range of problems. That's where you come in. I ask that you report on the efficacy of clamping on the problem(s) that you apply this script to. Please leave your comment on this page, or email it to


Comments and Ratings (4)


Hannes (view profile)

Trying this out for the Konka equation y=x1^2+x2^2-3x1-x1x2+3 in the range of (-1..3, -2..2), this optimizer does not finalize at the minimum (2,1), but at (3,2). Hereby (3,2) is the normalized (1,1) and the actual minimum (2,1) would be (0.75,0.75)

Why does the optimizer only try out Booleans 0 or 1, but no real values between 0..1?

Pikkin Lau

Potentially of great help, but what about providing an example of application?


md. (view profile)


Changed description. No changes to code.

Updated contact email. No change to code.

Updated description.

updated description

Updated description

MATLAB Release Compatibility
Created with R14
Compatible with any release
Platform Compatibility
Windows macOS Linux

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