Multiobjective optimization using evolutionary algorithms

@inproceedings{Sbalzarini2000MultiobjectiveOU,
  title={Multiobjective optimization using evolutionary algorithms},
  author={Ivo F. Sbalzarini and Sibylle D. M{\"u}ller and Petros Koumoutsakos},
  year={2000}
}
Evolutionary algorithms (EAs) such as evolution strategies and genetic algorithms have become the method of choice for optimization problems that are too complex to be solved using deterministic techniques such as linear programming or gradient (Jacobian) methods. The large number of applications (Beasley (1997)) and the continuously growing interest in this field are due to several advantages of EAs compared to gradient based methods for complex problems. EAs require little knowledge about the… CONTINUE READING
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