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This book contains state-of-the-art contributions in the field of
evolutionary and deterministic methods for design, optimization and
control in engineering and sciences. Specialists have written each
of the 34 chapters as extended versions of selected papers
presented at the International Conference on Evolutionary and
Deterministic Methods for Design, Optimization and Control with
Applications to Industrial and Societal Problems (EUROGEN 2013).
The conference was one of the Thematic Conferences of the European
Community on Computational Methods in Applied Sciences (ECCOMAS).
Topics treated in the various chapters are classified in the
following sections: theoretical and numerical methods and tools for
optimization (theoretical methods and tools; numerical methods and
tools) and engineering design and societal applications (turbo
machinery; structures, materials and civil engineering; aeronautics
and astronautics; societal applications; electrical and electronics
applications), focused particularly on intelligent systems for
multidisciplinary design optimization (mdo) problems based on
multi-hybridized software, adjoint-based and one-shot methods,
uncertainty quantification and optimization, multidisciplinary
design optimization, applications of game theory to industrial
optimization problems, applications in structural and civil
engineering optimum design and surrogate models based optimization
methods in aerodynamic design.
An overview of the most successful algorithms and techniques for
solving large, sparse systems of equations and some algorithms and
strategies for solving optimization problems. The most important
topics dealt with concern iterative methods, especially Krylov
methods, ordering techniques, and some iterative optimization
tools. The book is a compendium of theoretical and numerical
methods for solving large algebraic systems, special emphasis being
placed on convergence and numerical behaviour as affected by
rounding errors, accuracy in computing solutions for
ill-conditioned matrices, preconditioning effectiveness, ordering
procedures, stability factors, hybrid procedures and stopping
criteria. Recent advances in numerical matrix calculations are
presented, especially methods to accelerate the solution of
symmetric and unsymmetric linear systems. Convergence analysis of
the multi-grid method using a posteriori error estimation in second
order elliptic equations are presented. Some inverse problems are
also included. Evolution based software is described, such as
genetic algorithms and evolution strategies, relations and class
hierarchising to improve the exploration of large search spaces and
finding near-global optima. Recent developments in messy genetic
algorithms are also described. The tutorial nature of the book
makes it suitable for mathematicians, computer scientists,
engineers and postgraduates.
This book contains state-of-the-art contributions in the field of
evolutionary and deterministic methods for design, optimization and
control in engineering and sciences. Specialists have written each
of the 34 chapters as extended versions of selected papers
presented at the International Conference on Evolutionary and
Deterministic Methods for Design, Optimization and Control with
Applications to Industrial and Societal Problems (EUROGEN 2013).
The conference was one of the Thematic Conferences of the European
Community on Computational Methods in Applied Sciences (ECCOMAS).
Topics treated in the various chapters are classified in the
following sections: theoretical and numerical methods and tools for
optimization (theoretical methods and tools; numerical methods and
tools) and engineering design and societal applications (turbo
machinery; structures, materials and civil engineering; aeronautics
and astronautics; societal applications; electrical and electronics
applications), focused particularly on intelligent systems for
multidisciplinary design optimization (mdo) problems based on
multi-hybridized software, adjoint-based and one-shot methods,
uncertainty quantification and optimization, multidisciplinary
design optimization, applications of game theory to industrial
optimization problems, applications in structural and civil
engineering optimum design and surrogate models based optimization
methods in aerodynamic design.
An overview of the most successful algorithms and techniques for
solving large, sparse systems of equations and some algorithms and
strategies for solving optimization problems. The most important
topics dealt with concern iterative methods, especially Krylov
methods, ordering techniques, and some iterative optimization
tools. The book is a compendium of theoretical and numerical
methods for solving large algebraic systems, special emphasis being
placed on convergence and numerical behaviour as affected by
rounding errors, accuracy in computing solutions for
ill-conditioned matrices, preconditioning effectiveness, ordering
procedures, stability factors, hybrid procedures and stopping
criteria. Recent advances in numerical matrix calculations are
presented, especially methods to accelerate the solution of
symmetric and unsymmetric linear systems. Convergence analysis of
the multi-grid method using a posteriori error estimation in second
order elliptic equations are presented. Some inverse problems are
also included. Evolution based software is described, such as
genetic algorithms and evolution strategies, relations and class
hierarchising to improve the exploration of large search spaces and
finding near-global optima. Recent developments in messy genetic
algorithms are also described. The tutorial nature of the book
makes it suitable for mathematicians, computer scientists,
engineers and postgraduates.
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