That was a good question. The global optimization for this problem is to create a specific shape. In my opinion, there are at least 2 reasons why we use simulated annealing for this case: First of all, the search space is discrete so we are more likely to find the global optimum with simulated annealing. Secondly, the genetic algorithm can take a long time to converge while simulated annealing can give us a quick solution, which is ideal to create quick data for visualization

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