Optimization in Industry
Editat de Ian Parmee, Prabhat Hajelaen Limba Engleză Paperback – 6 aug 2002
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Specificații
ISBN-13: 9781852335342
ISBN-10: 1852335343
Pagini: 356
Ilustrații: XIV, 341 p. 58 illus.
Dimensiuni: 155 x 235 x 19 mm
Greutate: 0.5 kg
Ediția:Softcover reprint of the original 1st ed. 2002
Editura: SPRINGER LONDON
Colecția Springer
Locul publicării:London, United Kingdom
ISBN-10: 1852335343
Pagini: 356
Ilustrații: XIV, 341 p. 58 illus.
Dimensiuni: 155 x 235 x 19 mm
Greutate: 0.5 kg
Ediția:Softcover reprint of the original 1st ed. 2002
Editura: SPRINGER LONDON
Colecția Springer
Locul publicării:London, United Kingdom
Public țintă
ResearchCuprins
1 Industrial Integration.- 1.1. Optimization: The Competitive Edge.- 1.2. Optimization in Industry — What Does Industry Really Need?.- 1.3. Take-up and Adoption of Optimisation Technology for Engineering Design.- 1.4. Structural Optimization of Industrial Engineering Problems with General-purpose Optimization Procedures.- 2 Problem Representation Issues.- 2.1. Genetic Algorithms Solve Combinatorial Optimisation Problems in the Calibration of Combustion Engines.- 2.2. Integrated Computational Mechanics and Optimization for Design of Electronic Components.- 2.3. Robust Calibration of Computer Models of Engineering Networks with Limited Data.- 2.4. Aerodynamic Shape Optimisation Using Evolutionary Strategies.- 2.1. Time-saving Robust Design Considering Vehicle Crash Performance.- 2.2. Strategies for Structural and Thermal Optimization in the Field of Automotive Radio and Navigation Systems.- 3 Multi-objective Optimization.- 3.1. Optimal Positioning of Clamps for Workpiece Adjustment Using Multi-objective Evolutionary Computation.- 3.2. The Maximin Fitness Function for Multiobjective Evolutionary Optimization.- 3.3. Gas-assisted Injection Molding Optimisation with MOGA.- 3.4. Aerodynamic Optimization for the Transonic Compressor Stator Blade.- 4 Design Search and Exploration.- 4.1. The Direct Synthesis of Optimal Design Solutions for Complex Systems.- 4.2. Improving Cluster Oriented Genetic Algorithms for High- performance Region Identification.- 4.3. Search Efficiency in Genetic Algorithms.- 4.4. Evolutionary Computing Strategies for Preliminary Design Search and Exploration.- 5 General Applications.- 5.1. Improving the Optimisation of Engineering Structures Using the Self-designing Structures Approach.- 5.2. Running Characteristics of Spherical Plain Bearings for theOptimisation of Housings.- 5.3. An Optimization Model for Investment in Ethylene Derivatives.- 5.4. GA-Based Industrial Actuator Design for Optimum Control of Vibration in Flexible Structures.- 6 The Right Tools for the Job.- 6.1. Old and New Non-gradient Methods in Structural Engineering Optimisation.- 6.2. Multidisciplinary Design Optimisation of an Aircraft Wing by Applying a Hybrid Optimisation Strategy.- 6.3. Industrial Applications of Evolutionary Algorithms: A Comparison to Traditional Methods.- 6.4. Optimisation Techniques for Industrial Spring Design.- 7 Discussion Papers.- 7.1. Industrial Integration.- 7.2. Problem Representation in Design Optimisation.- 7.3. Multi-objective Optimization (MO).- 7.4. Detailed Design Optimisation.- Index of Contributors.
Caracteristici
Includes supplementary material: sn.pub/extras