Answers are grounded in this paper and cite their sources.
In this section, we will report on three applications of evolutionary algorithms (EA) in real world parameter optimization. These applications show how the principles, such as robustness and representation independence, make it possible to extend the scope of optimization algorithms available so far and find answers to problems where classical solution methods fail.Evolutionary algorithms are today a state-of-the-art methodology in solving hard optimization problems, and are regularly being used in industries such as automotive and aerospace. In fact, these algorithms have revolutionized the way hard problems are being solved today. The pioneers of evolutionary computation, including Larry Fogel as one the key founders of the field, have been laying the foundations with their creativity and visionary approach toward science.
No takes yet. Share an insight, caveat, or question.
Bäck et al. (2008) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: