It may not seem obvious at first glance, but computer science algorithms are often inspired by nature and biological processes. Some of these algorithms include neural networks, particle swarm optimization, artificial bee colony, ant colony optimization, evolutionary algorithms and many more. In fact, you can consider biological processes to be simply algorithms that nature have come up with to solve problems. From that point of view it's easy to see why many of these algorithms are optimization heuristics and metaheuristics. After all nature optimizes for survival. Heuristics, in case the term is not familiar to you, are algorithms that try to solve the problem faster by making some assumptions. As a result, heuristics are often not optimal but are more useful in cases when getting the best results take way too long. Metaheuristics take this to the next level -- they are a heuristic that generates or finds heuristics.