> But Based on my readings genetic algorithms are more known to be susceptible to local minima, while simulated annealing in theory is a global method. Both si

> But Based on my readings genetic algorithms are more known to be susceptible to local minima, while simulated annealing in theory is a global method. Both simulated annealing and genetic algorithms are global methods, and both can get caught in local minima. The same goes for pretty much every other global stochastic optimization method out there. Simulated annealing got this "special" reputation among engineers back in the '80s because the Metropolis algorithm had a formal proof of global guarantees -- run it long enough and it's guaranteed to find the global optimum. But nowadays most every algorithm in this category has similar guarantees. It's relatively easy to make such a guarantee as it turns out. I like differential evolution too, though it's pretty exploitative.