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Application of bionic optimization

  • To illustrate the power and the pitfalls of Bionic Optimization, we will show some examples spanning classes of applications and employing various strategies. These applications cover a broad range of engineering tasks. Nevertheless, there is no guarantee that our experiences and our examples will be sufficient to deal with all questions and issues in a comprehensive way. As general rule it might be stated, that for each class of problems, novices should begin with a learning phase. So, in this introductory phase, we use simple and quick examples, e.g., using small FE-models, linear load cases, short time intervals and simple material models. Here beginners within the Bionic Optimization community can learn which parameter combinations to use. In Sect. 3.​3 we discuss strategies for optimization study acceleration. Making use of these parameters as starting points is one way to set the specific ranges, e.g., number of parents and kids, crossing, mutation radii and, numbers of generations. On the other hand, these trial runs will doubtless indicate that Bionic Optimization needs large numbers of individual designs, and considerable time and computing power. We recommend investing enough time preparing each task in order to avoid the frustration should large jobs fail after long calculation times.

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Author of HS ReutlingenSteinbuch, Rolf; Kmitina, Iryna; Popova, Tatiana; Gekeler, Simon; Glück, Oskar; Srivastava, Ashish
Erschienen in:Bionic optimization in structural design : stochastically based methods to improve the performance of parts and assemblies
Place of publication:Berlin, Heidelberg
Editor:Rolf Steinbuch
Document Type:Book chapter
Publication year:2016
Page Number:23
First Page:101
Last Page:123
PPN:Im Katalog der Hochschule Reutlingen ansehen
DDC classes:620 Ingenieurwissenschaften und Maschinenbau
Open access?:Nein
Licence (German):License Logo  In Copyright - Urheberrechtlich geschützt