We've discussed a few traditional problem-solving strategies. Some of them guarantee finding the global solution, others don't, but they all share a common pattern. Either they guarantee discovering the global solution, but are too expensive (i.e., too time consuming) for solving typical real-world problems, or else they have a tendency of ``getting stuck'' in local optima. Since there is almost no chance to speed up algorithms that guarantee finding the global solution, i.e., there is almost no chance of finding polynomial-time algorithms for most real problems (as they tend to be NP-hard), the other remaining option aims at designing algorithms that are capable of escaping local optima.
CITATION STYLE
Michalewicz, Z., & Fogel, D. B. (2004). Escaping Local Optima. In How to Solve It: Modern Heuristics (pp. 115–134). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-07807-5_6
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