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Evolution Strategies and Other Methods

1992; Springer Nature; Linguagem: Inglês

10.1007/978-3-662-02830-8_9

1431-0066

Zbigniew Michalewicz,

Advanced Multi-Objective Optimization Algorithms

Evolution strategies (ESs) are algorithms which imitate the principles of natural evolution as a method to solve parameter optimization problems [7], [162]. They were developed in Germany during the 1960s. As stated in [162]: “In 1963 two students at the Technical University of Berlin met and were soon collaborating on experiments which used the wind tunnel of the Institute of Flow Engineering. During the search for the optimal shapes of bodies in a flow, which was then a matter of laborious intuitive experimentation, the idea was conceived of proceeding strategically. However, attempts with the coordinate and simple gradient strategies were unsuccessful. Then one of the students, Ingo Rechenberg, now Professor of Bionics and Evolutionary Engineering, hit upon the idea of trying random changes in the parameters defining the shape, following the example of natural mutations. The evolution strategy was born.” (The second student was Hans-Paul Schwefel, now Professor of Computer Science and Chair of System Analysis).