Cargando…

Evolutionary Computing in Advanced Manufacturing.

"This cutting-edge book covers emerging, evolutionary and nature inspired optimization techniques in the field of advanced manufacturing. The complexity of real life advanced manufacturing problems often cannot be solved by traditional engineering or computational methods. Hence, in recent year...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Tiwari, Manoj
Otros Autores: Harding, Jenny A.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Somerset : Wiley, 2011.
Temas:
Acceso en línea:Texto completo

MARC

LEADER 00000cam a2200000 4500
001 EBOOKCENTRAL_ocn947128132
003 OCoLC
005 20240329122006.0
006 m o d
007 cr |n|||||||||
008 160423s2011 xx o 000 0 eng d
040 |a EBLCP  |b eng  |e pn  |c EBLCP  |d OCLCQ  |d REDDC  |d OCLCF  |d K6U  |d OCLCQ  |d OCLCO 
020 |a 9781118161876 
020 |a 1118161874 
035 |a (OCoLC)947128132 
050 4 |a TS183  |b .E86 2011 
082 0 4 |a 658.80028563 
049 |a UAMI 
100 1 |a Tiwari, Manoj. 
245 1 0 |a Evolutionary Computing in Advanced Manufacturing. 
260 |a Somerset :  |b Wiley,  |c 2011. 
300 |a 1 online resource (285 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
588 0 |a Print version record. 
505 0 |a Cover; Half Title page; Title page; Copyright page; Preface; List of Contributors; Chapter 1: Production Planning Using Genetic Algorithm; 1.1 Introduction; 1.2 Production Planning Models; 1.3 Genetic Algorithm; 1.4 Implementation of GA; 1.5 Summary; Further Reading; Chapter 2: Process Planning through Ant Colony Optimization; 2.1 Introduction; 2.2 Ant Colony Optimization (ACO); References; Chapter 3: Introducing a Hybrid Genetic Algorithm for Integration of Set Up and Process Planning; 3.1 Introduction; 3.2 Process Planning; 3.3 Machine Set-up Time; 3.4 Chromosome Representation. 
505 8 |a 3.5 Fitness Value Evaluation3.6 Selection Operation; 3.7 Crossover Operations; 3.8 Mutation Operations (k-opt Exchange); 3.9 Conclusion; References; Chapter 4: Design for Supply Chain with Product Development Issues Using Cellular Particle Swarm Optimization (CPSO) Technique; 4.1 Introduction; 4.2 Problem Formulation; 4.3 Computational Analysis and Result; 4.4 Conclusions; References; Chapter 5: Genetic Algorithms with Chromosome Differentiation (GACD) Based Approach for Process Plan Selection Problems; 5.1 Introduction; 5.2 Problem Formulation. 
505 8 |a 5.3 Genetic Algorithm with Chromosome Differentiation5.4 GACD Based Solution Methodology to Process Plan Selection Problem; 5.5 Numerical Experiments; 5.6 Conclusions; References; Chapter 6: Operation Allocation in Flexible Manufacturing System Using Immune Algorithm; 6.1 Introduction; 6.2 Machine Loading Problem; 6.3 Solution Methodology; 6.4 Implementing Immune Algorithm for Machine Loading Problem; 6.5 Computational Result; 6.6 Conclusion; References; Chapter 7: Tool Selection in FMS A Hybrid SA-Tabu Algorithm Based Approach; 7.1 Introduction; 7.2 Literature Survey; 7.3 Problem Formulation. 
505 8 |a 7.4 Background on SA-Tabu Heuristic7.5 Implementation of Tabu-Simulated Annealing; 7.6 Test Cases; 7.7 Conclusion; References; Chapter 8: Integrating AGVs and Production Planning with Memetic Particle Swarm Optimization; 8.1 Introduction; 8.2 Literature Review; 8.3 Mathematical Model; 8.4 PSO and EMPSO; 8.5 Example; 8.6 Recombination (Local Search); 8.7 Summary; References; Chapter 9: Simulation-Based Aircraft Assembly Planning Using a Self-Guided Ant Colony Algorithm; 9.1 Introduction; 9.2 Background and Literature Survey; 9.3 Specifications of the Considered Aircraft Assembly. 
505 8 |a 9.4 Proposed Simulation-Based Assembly Planning Framework9.5 Experiment and Results; 9.6 Conclusion and Future Work; References; Chapter 10: Applications of Evolutionary Computing to Additive Manufacturing; 10.1 Introduction; 10.2 Design for Additive Manufacturing; 10.3 Data Handling; 10.4 Process Planning; 10.5 Concluding Remarks; References; Chapter 11: Multiple Fault Diagnosis Using Psycho-Clonal Algorithms; 11.1 Introduction; 11.2 Multiple Fault Diagnosis Problems; 11.3 Background of Psychoclonal Algorithm; 11.4 Numerical Experiments; 11.5 Conclusion; References. 
500 |a Chapter 12: Platform Formation Under Stochastic Demand. 
520 |a "This cutting-edge book covers emerging, evolutionary and nature inspired optimization techniques in the field of advanced manufacturing. The complexity of real life advanced manufacturing problems often cannot be solved by traditional engineering or computational methods. Hence, in recent years researchers and practitioners have proposed and developed new strands of advanced, intelligent techniques and methodologies. Evolutionary computing approaches are introduced in the context of a wide range of manufacturing activities, and through the examination of practical problems and their solutions, readers will gain confidence to apply these powerful computing solutions. The initial chapters introduce and discuss the well established evolutionary algorithm, to help readers to understand the basic building blocks and steps required to successfully implement their own solutions to real life advanced manufacturing problems. In the later chapters, modified and improved versions of evolutionary algorithms are discussed. The book concludes with appendices which provide general descriptions of several evolutionary algorithms"--  |c Provided by publisher 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
650 0 |a Evolutionary computation. 
650 0 |a Manufacturing processes  |x Data processing. 
650 6 |a Réseaux neuronaux à structure évolutive. 
650 6 |a Fabrication  |x Informatique. 
650 7 |a Evolutionary computation  |2 fast 
650 7 |a Manufacturing processes  |x Data processing  |2 fast 
700 1 |a Harding, Jenny A. 
776 0 8 |i Print version:  |a Tiwari, Manoj.  |t Evolutionary Computing in Advanced Manufacturing.  |d Somerset : Wiley, ©2011  |z 9781118161883 
856 4 0 |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=4032417  |z Texto completo 
936 |a BATCHLOAD 
938 |a ProQuest Ebook Central  |b EBLB  |n EBL4032417 
994 |a 92  |b IZTAP