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
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
Mark H.A. Davis introduced the Piecewise-Deterministic Markov Process (PDMP) class of stochastic hybrid models in an article in 1984. Today it is used to model a variety of complex systems in the fields of engineering, economics, management sciences, biology, Internet traffic, networks and many more. Yet, despite this, there is very little in the way of literature devoted to the development of numerical methods for PDMDs to solve problems of practical importance, or the computational control of PDMPs.
This book therefore presents a collection of mathematical tools that have been recently developed to tackle such problems. It begins by doing so through examples in several application domains such as reliability. The second part is devoted to the study and simulation of expectations of functionals of PDMPs. Finally, the third part introduces the development of numerical techniques for optimal control problems such as stopping and impulse control problems.
Автор: Panos M. Pardalos; Anatoly Zhigljavsky; Julius ?il Название: Advances in Stochastic and Deterministic Global Optimization ISBN: 3319299735 ISBN-13(EAN): 9783319299730 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Current research results in stochastic and deterministic global optimization including single and multiple objectives are explored and presented in this book by leading specialists from various fields. Contributions include applications to multidimensional data visualization, regression, survey calibration, inventory management, timetabling, chemical engineering, energy systems, and competitive facility location. Graduate students, researchers, and scientists in computer science, numerical analysis, optimization, and applied mathematics will be fascinated by the theoretical, computational, and application-oriented aspects of stochastic and deterministic global optimization explored in this book.
This volume is dedicated to the 70th birthday of Antanas ?ilinskas who is a leading world expert in global optimization. Professor ?ilinskas's research has concentrated on studying models for the objective function, the development and implementation of efficient algorithms for global optimization with single and multiple objectives, and application of algorithms for solving real-world practical problems.
Автор: Daniel Scholz Название: Deterministic Global Optimization ISBN: 1489995552 ISBN-13(EAN): 9781489995551 Издательство: Springer Рейтинг: Цена: 16070.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines geometric branch-and-bound methods, such as in Lipschitzian optimization, d.c. programming and interval analysis, introduces a new concept for the rate of convergence and also analyzes several bounding operations reported in the literature.
Автор: Kevin L. Moore Название: Iterative Learning Control for Deterministic Systems ISBN: 1447119142 ISBN-13(EAN): 9781447119142 Издательство: Springer Рейтинг: Цена: 13060.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The text follows with a complete and unifying analysis of the learning control problem for linear LTI systems using a system-theoretic approach which offers insight into the nature of the solution of the learning control problem.
Автор: Kevin Warwick; Miroslav Karny; Alena Halouskova Название: Advanced Methods in Adaptive Control for Industrial Applications ISBN: 3540538356 ISBN-13(EAN): 9783540538356 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The seminar papers which comprise this book deal with advanced methods in adaptive control in industrial applications. Real time computer control methods are considered and system resilience is viewed as an important factor.
Описание: Surveying advances in optimization and control methods with applications to industrial engineering and construction management, this book covers lean and agile construction project management, set splitting problems, distributed fault detection and more.
Автор: Hime Aguiar e Oliveira Junior Название: Evolutionary Global Optimization, Manifolds and Applications ISBN: 3319264664 ISBN-13(EAN): 9783319264660 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents powerful techniques for solving global optimization problems on manifolds by means of evolutionary algorithms, and shows in practice how these techniques can be applied to solve real-world problems. Here, these problems are reformulated as constrained global optimization tasks and solved with the help of Fuzzy ASA.
Описание: Surveying advances in optimization and control methods with applications to industrial engineering and construction management, this book covers lean and agile construction project management, set splitting problems, distributed fault detection and more.
Автор: Ernesto Sanchez; Giovanni Squillero; Alberto Tonda Название: Industrial Applications of Evolutionary Algorithms ISBN: 364244346X ISBN-13(EAN): 9783642443466 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Ideal as a reference both for experienced users and novices, this publication combines a thorough introduction to evolutionary computation with details of its application to real-world problems and advice on tackling a wealth of issues in its implementation.
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