Evolutionary Strategies for Multidisciplinary ... - Dynardo GmbH

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Operators: Selection Example: (2,3)-Selection Example: (2+3)-Selection Parents don‘t survive … Parents don‘t survive! … but a worse offspring. … now this offspring survives. 20
Operators: Selection Possible occurrences of selection Exception! (1+1)-ES: One parent, one offspring, 1/5-Rule (1,λ)-ES: One Parent, λ offspring Example: (1,10)-Strategy One step size / n self-adaptive step sizes Mutative step size control Derandomized strategy (μ,λ)-ES: μ > 1 parents, λ > μ offspring Example: (2,15)-Strategy Includes recombination Can overcome local optima (μ+λ)-strategies: elitist strategies 21
Page 1 and 2: Evolutionary Strategies for Multidi
Page 3 and 4: Background I Biology = Engineering
Page 5 and 6: Optimization f : objective function
Page 7 and 8: Dynamic Optimization Dynamic Functi
Page 9 and 10: The Fundamental Challenge Global co
Page 11 and 12: Evolution Strategies 11
Page 13 and 14: Evolution Strategy - Basics Mostly
Page 15 and 16: Evolution Strategy: Algorithms Muta
Page 17 and 18: Operators: Mutation - one σ Thereb
Page 19: Evolution Strategy Algorithms Selec
Page 23 and 24: Self-adaptation Self adaptation No
Page 25 and 26: Self-adaptation Self adaptation: :
Page 27 and 28: Mixed-Integer Mixed Integer Evoluti
Page 29 and 30: Mixed-Integer Mixed Integer ES: Mut
Page 31 and 32: Multidisciplinary Optimization (MDO
Page 33 and 34: MDO Crash / Statics / Dynamics Mini
Page 35 and 36: MDO Production Runs (II) Mass NuTec
Page 37 and 38: MDO ASF ® Front Optimization Pre-o
Page 39 and 40: MDO Run Comparison Initial design,
Page 41: Corporate Headquarters: Charlotte,

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