Notes on the Simulated Binary Crossover Operator

The Simulated Binary Crossover (SBX) is a well known variation operator for genetic real-valued optimization. It's surprising that I never came to implement this before, since I've been working with GAs for three years.

This is a remarkably elegant operator which was specifically designed to preserve the properties of the one-point crossover used for binary-coded GA optimization:

1) The average of the generated values is approximately the same of the original values before crossover; and

2) The probability of a spread factor value of betha = 1 is higher than for other spread factor values, what yeilds a stationary crossover operator.

That's such a great thing that I'm finally merging it into my NSGA2 implementation for numerical optimization benchmark. To find out more, go through the following slides:

Simulated Binary Crossover

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