Preface.- Part 1: Theoretical and Numerical Methods and Tools for Optimization.- 1.1 Theoretical Methods and Tools.- 1.1.1 Multi-Objective Evolutionary Algorithms in Real-World Applications: Some Recent Results and Current Challenges, by Carlos A. Coello Coello.- 1.1.2 Hybrid Optimization Algorithms and Hybrid Response Surfaces, by George S. Dulikravich and Marcelo J. Colaco.- 1.1.3 A genetic algorithm for a sensor device location problem, by Egidio D'Amato, Elia Daniele and Lina Mallozzi.- 1.1.4 The Role of Artificial Neural Networks in Evolutionary Optimization: A Review, by Mustapha Maarouf, Adriel Sosa, Blas Galvбn, David Greiner, Gabriel Winter, Mбximo Mendez and Ricardo Aguasca.- 1.1.5 Reliability-based Design Optimization with the Generalized Inverse Distribution Function, by Domenico Quagliarella, Giovanni Petrone and Gianluca Iaccarino.- 1.2 Numerical Methods and Tools.- 1.2.1 On the choice of surrogates for multilevel aircraft performance models, by Manon Bondouy, Sophie Jan, Serge Laporte and Christian Bes.- 1.2.2 Multi-objective design optimization using high-order statistics for CFD applications, by Pietro M. Congedo, Gianluca Geraci, Remi Abgrall and Gianluca Iaccarino.- 1.2.3 Extension of the One-Shot Method for Optimal Control with Unsteady PDEs, by Stefanie Gunther, Nicolas R. Gauger and Qiqi Wang.- 1.2.4 Adaptive Aerodynamic Design Optimization for Navier-Stokes using Shape Derivatives with Discontinuous Galerkin Methods, by Lena Kaland, Matthias Sonntag and Nicolas R. Gauger.- 1.2.5 Optimal Flow Control and Topology Optimization Using the Continuous Adjoint Method in Unsteady Flows, by Ioannis S. Kavvadias, George K. Karpouzas, Evangelos M. Paoutsis-Kiachagias, Dimitris I. Papadimitrou and Kyriakos C. Giannakoglou.- Part 2: Engineering Design and Societal Applications.- 2.1 Turbomachinery.- 2.1.1 Design optimization of the Primary Pump of a Nuclear Reactor, by Tom Verstraete and Lasse Mueller.- 2.1.2 Direct 3D Aerodynamic Optimization of Turbine Blades with GPU-accelerated CFD, by Philipp Amtsfeld, Dieter Bestle and Marcus Meyer.- 2.1.3 Evaluation of Surrogate Modelling Methods for Turbo-Machinery Component Design Optimization, by Gianluca Badjan, Carlo Poloni, Andrew Pike and Nadir Ince.- 2.1.4 Robust Aerodynamic Design Optimization of Horizontal Axis Wind Turbine Rotors, by Marco Caboni, Edmondo Minisci and Michele Sergio Campobaso.- 2.1.5 Horizontal axis hydroturbine shroud airfoil optimization, by Elia Daniele, Elios Ferrauto and Domenico P. Coiro.- 2.1.6 Parametric Blending and FE-Optimization of a Compressor Blisk Test Case, by Kai Karger and Dieter Bestle.- 2.1.7 Modular Automated Aerodynamic Compressor Design Process, by Fiete Poehlmann, Dieter Bestle, Peter Flassig and Michиl Hinz.- 2.1.8 Design-Optimization of a Compressor Blading on a GPU Cluster, by Konstantinos T. Tsiakas, Xenofon S. Trompoukis, Varvara G. Asouti and Kyriakos C. Giannakoglou.- 2.2 Structures, Materials and Civil Engineering.- 2.2.1 Immune and Swarm Optimization of Structures, by Tadeusz Burczyński, Arkadiusz Poteralski and Miroslaw Szczepanik.- 2.2.2 Investigation of three genotypes for mixed variable evolutionary optimization, by Rajan Filomeno Coelho, Manyu Xiao, Aurore Guglielmetti, Manuel Herrera and Weihong Zhang.- 2.2.3 A Study of Nash-Evolutionary Algorithms for Reconstruction Inverse Problems in Structural Engineering, by David Greiner, Jacques Pйriaux, Josй Marнa Emperador, Blas Galvбn and Gabriel Winter.- 2.2.4 A comparative study on design optimization of polygonal and Bйzier curve-shaped thin noise barriers using dual BEMformulation, by Rayco Toledo, Juan J. Aznбrez, Orlando Maeso and David Greiner.- 2.2.5 A Discrete Adjoint Approach For Trailing-Edge Noise Minimization using Porous Material, by Beckett Y. Zhou, Nicolas R. Gauger, Seong R. Koh and Wolfgang Schrцder.- 2.3 Aeronautics and Astronautics.- 2.3.1 Conceptual Design of Single-Stage Launch Vehicle with Hybrid Rocket Engine Using Desi
Preface.- Part 1: Theoretical and Numerical Methods and Tools for Optimization.- 1.1 Theoretical Methods and Tools.- 1.1.1 Multi-Objective Evolutionary Algorithms in Real-World Applications: Some Recent Results and Current Challenges, by Carlos A. Coello Coello.- 1.1.2 Hybrid Optimization Algorithms and Hybrid Response Surfaces, by George S. Dulikravich and Marcelo J. Colaco.- 1.1.3 A genetic algorithm for a sensor device location problem, by Egidio D'Amato, Elia Daniele and Lina Mallozzi.- 1.1.4 The Role of Artificial Neural Networks in Evolutionary Optimization: A Review, by Mustapha Maarouf, Adriel Sosa, Blas Galvбn, David Greiner, Gabriel Winter, Mбximo Mendez and Ricardo Aguasca.- 1.1.5 Reliability-based Design Optimization with the Generalized Inverse Distribution Function, by Domenico Quagliarella, Giovanni Petrone and Gianluca Iaccarino.- 1.2 Numerical Methods and Tools.- 1.2.1 On the choice of surrogates for multilevel aircraft performance models, by Manon Bondouy, Sophie Jan, Serge Laporte and Christian Bes.- 1.2.2 Multi-objective design optimization using high-order statistics for CFD applications, by Pietro M. Congedo, Gianluca Geraci, Remi Abgrall and Gianluca Iaccarino.- 1.2.3 Extension of the One-Shot Method for Optimal Control with Unsteady PDEs, by Stefanie Gunther, Nicolas R. Gauger and Qiqi Wang.- 1.2.4 Adaptive Aerodynamic Design Optimization for Navier-Stokes using Shape Derivatives with Discontinuous Galerkin Methods, by Lena Kaland, Matthias Sonntag and Nicolas R. Gauger.- 1.2.5 Optimal Flow Control and Topology Optimization Using the Continuous Adjoint Method in Unsteady Flows, by Ioannis S. Kavvadias, George K. Karpouzas, Evangelos M. Paoutsis-Kiachagias, Dimitris I. Papadimitrou and Kyriakos C. Giannakoglou.- Part 2: Engineering Design and Societal Applications.- 2.1 Turbomachinery.- 2.1.1 Design optimization of the Primary Pump of a Nuclear Reactor, by Tom Verstraete and Lasse Mueller.- 2.1.2 Direct 3D Aerodynamic Optimization of Turbine Blades with GPU-accelerated CFD, by Philipp Amtsfeld, Dieter Bestle and Marcus Meyer.- 2.1.3 Evaluation of Surrogate Modelling Methods for Turbo-Machinery Component Design Optimization, by Gianluca Badjan, Carlo Poloni, Andrew Pike and Nadir Ince.- 2.1.4 Robust Aerodynamic Design Optimization of Horizontal Axis Wind Turbine Rotors, by Marco Caboni, Edmondo Minisci and Michele Sergio Campobaso.- 2.1.5 Horizontal axis hydroturbine shroud airfoil optimization, by Elia Daniele, Elios Ferrauto and Domenico P. Coiro.- 2.1.6 Parametric Blending and FE-Optimization of a Compressor Blisk Test Case, by Kai Karger and Dieter Bestle.- 2.1.7 Modular Automated Aerodynamic Compressor Design Process, by Fiete Poehlmann, Dieter Bestle, Peter Flassig and Michиl Hinz.- 2.1.8 Design-Optimization of a Compressor Blading on a GPU Cluster, by Konstantinos T. Tsiakas, Xenofon S. Trompoukis, Varvara G. Asouti and Kyriakos C. Giannakoglou.- 2.2 Structures, Materials and Civil Engineering.- 2.2.1 Immune and Swarm Optimization of Structures, by Tadeusz Burczyński, Arkadiusz Poteralski and Miroslaw Szczepanik.- 2.2.2 Investigation of three genotypes for mixed variable evolutionary optimization, by Rajan Filomeno Coelho, Manyu Xiao, Aurore Guglielmetti, Manuel Herrera and Weihong Zhang.- 2.2.3 A Study of Nash-Evolutionary Algorithms for Reconstruction Inverse Problems in Structural Engineering, by David Greiner, Jacques Pйriaux, Josй Marнa Emperador, Blas Galvбn and Gabriel Winter.- 2.2.4 A comparative study on design optimization of polygonal and Bйzier curve-shaped thin noise barriers using dual BEMformulation, by Rayco Toledo, Juan J. Aznбrez, Orlando Maeso and David Greiner.- 2.2.5 A Discrete Adjoint Approach For Trailing-Edge Noise Minimization using Porous Material, by Beckett Y. Zhou, Nicolas R. Gauger, Seong R. Koh and Wolfgang Schrцder.- 2.3 Aeronautics and Astronautics.- 2.3.1 Conceptual Design of Single-Stage Launch Vehicle with Hybrid Rocket Engine Using Desi
Описание: 1. Keynote: Risk, Optimization and Meanfield Type Control, by Olivier Pironneau and Mathieu Lauriиre.- 2. Surrogate-Based Optimization in Aerodynamic Design.- A Review of Surrogate Modeling Techniques for Aerodynamic Analysis and Optimization: Current Limitations and Future Challenges in Industry, by Raul Yondo, Kamil Bobrowski, Esther Andrйs and Eusebio Valero.- Constrained Single-Point Aerodynamic Shape Optimization of the DPW-W1 wing through Evolutionary Programming and Support Vector Machines, by E. Andrйs-Pйrez, D. Gonzбlez-Juбrez, M. J. Martin-Burgos, L. Carro-Calvo.- Enabling of Large Scale Aerodynamic Shape Optimization through POD-based Reduced-Order Modeling and Free Form Deformation, by A. Scardigli, R. Arpa, A. Chiarini and H. Telib.- Application of Surrogate-based Optimization Techniques to Aerodynamic Design Cases, by Emiliano Iuliano and Domenico Quagliarella.- Efficient Global Optimization method for multipoint airfoil design, by Davide Cinquegrana and Emiliano Iuliano.- 3. Adjoint Methods for Steady and Unsteady Optimization.- Checkpointing with time gaps for unsteady adjoint CFD, by Jan Christian Hueckelheim and Jens-Dominik Mueller.- Shape Optimization ofWind Turbine Blades using the Continuous Adjoint Method and Volumetric NURBS on a GPU Cluster, by Konstantinos T. Tsiakas, Xenofon S. Trompoukis, Varvara G. Asouti and Kyriakos C. Giannakoglou.- Aerodynamic Shape Optimization Using the Adjoint-based Truncated Newton Method, by Evangelos M. Papoutsis-Kiachagias, Mehdi Ghavami Nejad, and Kyriakos C. Giannakoglou.- Application of the adjoint method for the reconstruction of the boundary condition in unsteady shallow water flow simulation, by Asier Lacasta, Daniel Caviedes-Voulliиme and Pilar Garcнa-Navarro.- Aerodynamic Optimization of Car Shapes using the Continuous Adjoint Method and an RBF Morpher, by E.M. Papoutsis-Kiachagias, S. Porziani, C. Groth, M.E. Biancolini, E. Costa and K.C. Giannakoglou.- 4. Holistic Optimization in Marine Design.- Upfront CAD - Parametric modeling techniques for shape optimization, by S. Harries, C. Abt and M. Brenner.- Simulation-based Design Optimization by Sequential Multi-criterion Adaptive Sampling and Dynamic Radial Basis Functions, by Matteo Diez, Silvia Volpi, Andrea Serani, Frederick Stern and Emilio F. Campana.- Application of Holistic Ship Optimization in Bulkcarrier Design and Operation, by Lampros Nikolopoulos, Evangelos Boulougouris.- 5. Game Strategies Combined with Evolutionary Computation.- Designing Networks in Cooperation with ACO, by E. D'Amato, E. Daniele and L. Mallozzi.- Augmented Lagrangian approach for constrained potential Nash games, by Lina Mallozzi and Domenico Quagliarella.- A Diversity Dynamic Territory Nash Strategy in Evolutionary Algorithms: Enhancing Performances in Reconstruction Problems in Structural Engineering, by David Greiner, Jacques Pйriaux, J.M. Emperador, B. Galvбn, G. Winter.- Interactive Inverse Modeling Based Multiobjective Evolutionary Algorithm, by Karthik Sindhya and Jussi Hakanen.- Multi-Disciplinary Design Optimization of Air-breathing Hypersonic Vehicle Using Pareto Games and Evolutionary Algorithms, by Peng Wu, Zhili Tang, Jacques Periaux.- 6. Optimisation under Uncertainty.- Innovative methodologies for Robust Design Optimization with large number of uncertainties using modeFRONTIER, by Alberto Clarich, Rosario Russo.- A Novel Method for Inverse Uncertainty Propagation, by Xin Chen, ArturoMolina-Crist obal, Marin D. Guenov, Varun C. Datta, Atif Riaz.- Uncertainty Sources in the Baseline Configuration for Robust Design of a Supersonic Natural Laminar Flow Wing-Body, by Domenico Quagliarella and Emiliano Iuliano.- Robust Airfoil Design in the Context of Multi-Objective Optimization, by Lisa Kusch and Nicolas R. Gauger.- An alternative formulation for design under uncertainty, by F. Fusi and P. M. Congedo and G. Geraci and G. Iaccarino.- Polynomial Representation of Model Uncertainty in Dynamical
Автор: D.E. Grierson; P. Hajela Название: Emergent Computing Methods in Engineering Design ISBN: 3540608737 ISBN-13(EAN): 9783540608738 Издательство: Springer Рейтинг: Цена: 34799.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Includes papers that show the tremendous potential of emerging computing paradigms such as genetic algorithms, evolutionary computing, and neural networks for solving problems of engineering design.
Автор: Pravir K. Chawdhry; Rajkumar Roy; Raj K. Pant Название: Soft Computing in Engineering Design and Manufacturing ISBN: 3540762140 ISBN-13(EAN): 9783540762140 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Soft Computing has emerged as an important approach towards achieving intelligent computational paradigms where key elements are learning from experience in the presence of uncertainties, fuzzy belief functioos, and *evolutioo of the computing strategies of the learning agent itself.
Автор: D.E. Grierson; P. Hajela Название: Emergent Computing Methods in Engineering Design ISBN: 3642082394 ISBN-13(EAN): 9783642082399 Издательство: Springer Рейтинг: Цена: 34799.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume contains the text of papers presented at the NATO Advanced Research Workshop on Emergent Computing Methods in Engineering Design, held in Nafplio, Greece, August 25-27, 1994. The workshop convened together some thirty or so researchers from Canada, France, Germany, Greece, Israel, Taiwan, The Netherlands, United Kingdom and the United States of America, to address issues related to the application of such emergent computing methods as genetic algorithms, neural networks and simulated annealing in problems of engineering design. The volume is essentially organized into three parts, with each part having some theoretical papers and other papers of a more practical nature. The frrst part, which comprises the largest number of papers, deals with genetic algorithms and evolutionary computing and presents subject matter ranging from proposed improvements to the computing methodology to specific applications in engineering design. The second part deals with neural networks and considers such topics as their application as approximation tools in design, their adaptation in control system design and theoretical issues of interpretation. The third part of the volume presents a collection of papers that examine such diverse topics as the combined use of genetic algorithms and neural networks, the application of simulated annealing techniques, problem decomposition techniques and the computer recognition and interpretation of emerging objects in engineering design.
Описание: The volume is a collection of high-quality peer-reviewed research papers presented in the International Conference on Artificial Intelligence and Evolutionary Computation in Engineering Systems (ICAIECES 2016) held at SRM University, Chennai, Tamilnadu, India.
Автор: I.C. Parmee Название: Adaptive Computing in Design and Manufacture VI ISBN: 1852338296 ISBN-13(EAN): 9781852338299 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Adaptive Computing in Design and Manufacture conference series has become a well-established, largely application-oriented meeting recognised by several UK Engineering Institutions and the International Society of Genetic and Evolutionary Computing.
Автор: I.C. Parmee Название: Adaptive Computing in Design and Manufacture V ISBN: 1852336056 ISBN-13(EAN): 9781852336059 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The Adaptive Computing in Design and Manufacture Conference series is now in its tenth year and has become a well-established, application-oriented meeting recognised by several UK Engineering Institutions and the International Society of Genetic and Evolutionary Computing.
Автор: Ian C. Parmee Название: Adaptive Computing in Design and Manufacture ISBN: 354076254X ISBN-13(EAN): 9783540762546 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The third evolutionary I adaptive computing conference organised by the Plymouth Engineering Design Centre (PEDC) at the University of Plymouth again explores the utility of various adaptive search algorithms and complementary computational intelligence techniques within the engineering design and manufacturing domains.
Автор: Dipankar Dasgupta; Zbigniew Michalewicz Название: Evolutionary Algorithms in Engineering Applications ISBN: 3642082823 ISBN-13(EAN): 9783642082825 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book is a collection of high-quality peer-reviewed research papers presented in the International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES 2017).
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