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Simulated annealing isn't technically a genetic algorithm (nor is random perturbation). Simulated annealing jiggles things randomly (in this case, probably locations of LUTs), with decreasing amplitude over time. The amplitude of the random perturbations is the "temperature," which decreases until the system has settled into a (hopefully global) optimum. So basically this system will start moving the LUTs around a lot, keeping the most optimal results, and gradually start moving them around less and less until the result doesn't change for a while.

A genetic algorithm, by contrast, encodes the system into a "string" (like a DNA strand), and then swaps pieces of strings between two "organisms," just like genetic mating does. The most optimal descendants are kept, the least are discarded, and the process is repeated. This would be harder to implement for locations, as you would have to encode locations onto a string, and be able to swap pieces of strings while maintaining the functionality of the LUTs.




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