Multi-objective Evolutionary Optimisation for Product Design and Manufacturing [recurso electrónico] / edited by Lihui Wang, Amos H. C. Ng, Kalyanmoy Deb.

Por: Wang, Lihui [editor.]Colaborador(es): Ng, Amos H. C [editor.] | Deb, Kalyanmoy [editor.] | SpringerLink (Online service)Tipo de material: TextoTextoEditor: London : Springer London, 2011Descripción: XV, 505 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9780857296528Tema(s): Engineering | Computer simulation | Computer aided design | Machinery | Engineering | Manufacturing, Machines, Tools | Simulation and Modeling | Computer-Aided Engineering (CAD, CAE) and DesignFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 670 Clasificación LoC:TJ241Recursos en línea: Libro electrónicoTexto
Contenidos:
1. Multi-objective Optimisation Using Evolutionary Algorithms: An Introduction -- 2. Multi-objective Optimisation in Manufacturing Supply-chain Systems -- 3. State-of-the-Art Multi-objective Optimisation of Manufacturing Processes Based on Thermo-mechanical Simulations -- 4. Many-objective Evolutionary Optimisation and Visual Analytics for Product Family Design -- 5. Product Portfolio Selection of Designs Through an Analysis of Lower-dimensional Manifolds and Identification of Common Properties -- 6. Multi-objective Optimisation of a Family of Industrial Robots -- 7. Multi-objective Optimisation and Multi-criteria Decision -- 8. A Setup Planning Approach Considering Tolerance Cost Factors -- 9. Preference Vector Ant Colony System for Minimising Make-span and Energy Consumption in a Hybrid Flow Shop -- 10. Intelligent Optimisation for Integrated Process Planning and Scheduling -- 11. Distributed Real-time Scheduling by Using Multi-agent Reinforcement Learning -- 12. A Multiple Ant Colony Optimisation Approach for a Multi-objective Manufacturing Rescheduling Problem -- 13. Reconfigurable Facility Layout Design for Job-shop Assembly Operations -- 14. A Simulation Optimisation Framework for Container Terminal Layout Design -- 15. Simulation-based Innovisation Using Data Mining for Production Systems Analysis -- 16. Multi-objective Production Systems Optimisation with Investment and Running Cost -- 17. Supply Chain Design Using Simulation-based NSGA-II Approach.
En: Springer eBooksResumen: With the increasing complexity and dynamism in today’s product design and manufacturing, more optimal, robust and practical approaches and systems are needed to support product design and manufacturing activities. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing presents a focused collection of quality chapters on state-of-the-art research efforts in multi-objective evolutionary optimisation, as well as their practical applications to integrated product design and manufacturing. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing consists of two major sections. The first presents a broad-based review of the key areas of research in multi-objective evolutionary optimisation. The second gives in-depth treatments of selected methodologies and systems in intelligent design and integrated manufacturing. Recent developments and innovations in multi-objective evolutionary optimisation make Multi-objective Evolutionary Optimisation for Product Design and Manufacturing a useful text for a broad readership, from academic researchers to practicing engineers.
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Libro Electrónico Biblioteca Electrónica
Colección de Libros Electrónicos TJ241 (Browse shelf(Abre debajo)) 1 No para préstamo 370607-2001

1. Multi-objective Optimisation Using Evolutionary Algorithms: An Introduction -- 2. Multi-objective Optimisation in Manufacturing Supply-chain Systems -- 3. State-of-the-Art Multi-objective Optimisation of Manufacturing Processes Based on Thermo-mechanical Simulations -- 4. Many-objective Evolutionary Optimisation and Visual Analytics for Product Family Design -- 5. Product Portfolio Selection of Designs Through an Analysis of Lower-dimensional Manifolds and Identification of Common Properties -- 6. Multi-objective Optimisation of a Family of Industrial Robots -- 7. Multi-objective Optimisation and Multi-criteria Decision -- 8. A Setup Planning Approach Considering Tolerance Cost Factors -- 9. Preference Vector Ant Colony System for Minimising Make-span and Energy Consumption in a Hybrid Flow Shop -- 10. Intelligent Optimisation for Integrated Process Planning and Scheduling -- 11. Distributed Real-time Scheduling by Using Multi-agent Reinforcement Learning -- 12. A Multiple Ant Colony Optimisation Approach for a Multi-objective Manufacturing Rescheduling Problem -- 13. Reconfigurable Facility Layout Design for Job-shop Assembly Operations -- 14. A Simulation Optimisation Framework for Container Terminal Layout Design -- 15. Simulation-based Innovisation Using Data Mining for Production Systems Analysis -- 16. Multi-objective Production Systems Optimisation with Investment and Running Cost -- 17. Supply Chain Design Using Simulation-based NSGA-II Approach.

With the increasing complexity and dynamism in today’s product design and manufacturing, more optimal, robust and practical approaches and systems are needed to support product design and manufacturing activities. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing presents a focused collection of quality chapters on state-of-the-art research efforts in multi-objective evolutionary optimisation, as well as their practical applications to integrated product design and manufacturing. Multi-objective Evolutionary Optimisation for Product Design and Manufacturing consists of two major sections. The first presents a broad-based review of the key areas of research in multi-objective evolutionary optimisation. The second gives in-depth treatments of selected methodologies and systems in intelligent design and integrated manufacturing. Recent developments and innovations in multi-objective evolutionary optimisation make Multi-objective Evolutionary Optimisation for Product Design and Manufacturing a useful text for a broad readership, from academic researchers to practicing engineers.

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