Soft computing methodologies for structural optimization

Soft computing methodologies for structural optimization

The paper examines the efficiency of soft computing techniques in structural optimization, in particular algorithms based on evolution strategies combined with neural networks, for solving large-scale, continuous or discrete structural optimization problems. The proposed combined algorithms are implemented both in deterministic and reliability based structural optimization problems, in an effor...

Soft computing in bioinformatics: Methodologies and applications

Bioinformatics, an area that has evolved in response to this deluge of information, can be viewed as the use of computational methods to handle biological data. It is an interdisciplinary field involving biology, computer science, mathematics and statistics to analyze biological sequence data, genome content & arrangement, and to predict the function and structure of macromolecules. Soft comput...

Intelligent Control Systems Using Soft Computing Methodologies

Soft computing methods for applied shape optimization

vided the structural mechanics computations in the joint paper [135]. Beyond the fruitful cooperation, my special thanks go to Sebastian for helping out many times in any kind of issue related to this dissertation. I also appreciate the Deutsche Forschungsgemeinschaft (DFG) for financial support in the Graduiertenkolleg 853 " Modellierung, Simulation und Optimierung von Ingenieuranwen-dungen " .

Multi-agent simulation using discrete event and soft-computing methodologies

IVith tl7e emerging applications of multi-agent systems, there is aluays a need for simulation to i~ertfi the results before actual implementation. Multi-agent sintulafion provides a test bed for several soflcompziting algorithms like f i z zy logic, learning automata, evolutionary olgorithms, etc. In this paper we discuss the fusion of these saff-computing methodologies and existing tools for ...