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Submit a ProposalEvolutionary Computing in Advanced Manufacturing
 | Edited by Manoj Tiwari and Jenny A. Harding Copyright: 2011 | Expected Pub Date:06/16/2011 ISBN: 9780470639245 | Hardcover | 352 pages | 128 illustrations Price: $183 USD  |
One Line Description
This cutting-edge book covers emerging, evolutionary and nature inspired optimization techniques in the field of advanced manufacturing
Audience
Manufacturing engineers in academic and industry as well as IT/Computer Science specialists involved in manufacturing. Also Students at MSc and PhD levels.
All large and medium-sized corporations in manufacturing or manufacturing-related industries with complex planning problems will need this book.
Manufacturing engineers in academic and industry as well as IT/Computer Science specialists involved in manufacturing. Also Students at MSc and PhD levels.
All large and medium-sized corporations in manufacturing or manufacturing-related industries with complex planning problems will need this book.
Description
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.
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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.
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Author / Editor Details
Manoj Tiwari is based in the Department of Industrial Engineering and Management, the Indian Institute of Technology, Kharagpur. He is an acknowledged research leader and has worked in the areas of evolutionary computing, applications, modeling and simulation of manufacturing system, supply chain management, planning and scheduling of automated manufacturing system for about 20 years. He has published more than 150 articles in leading international journals and serves on the editorial board Member of 11 international journals. He is the associate editor of Journal of Intelligent Manufacturing and International Journal of System Science.
Manoj Tiwari is based in the Department of Industrial Engineering and Management, the Indian Institute of Technology, Kharagpur. He is an acknowledged research leader and has worked in the areas of evolutionary computing, applications, modeling and simulation of manufacturing system, supply chain management, planning and scheduling of automated manufacturing system for about 20 years. He has published more than 150 articles in leading international journals and serves on the editorial board Member of 11 international journals. He is the associate editor of Journal of Intelligent Manufacturing and International Journal of System Science.
Jenny A. Harding joined the Wolfson School of Mechanical and Manufacturing Engineering,Loughborough University in 1992 after working in industry for many years. Her industrial experience includes textile production and engineering, and immediately prior to joining Loughborough University, she spent 7 years working in R&D at Rank Taylor Hobson Ltd., manufacturers of metrology instruments. Her experience is mostly in the areas of mathematics and computing for manufacturing.
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Table of Contents
Preface.
1. Production Planning Using Genetic Algorithm:
S. K. Kumar and M. K. Tiwari.
2. Process Planning Through Ant Colony Optimization:
Puneet Bhardwaj and M. K.Tiwari.
3. Introducing a Hybrid Genetic Algorithm for Integration of Set Up and Process Planning:
S.H. Chung and F.T.S. Chan.
4. Design for Supply Chain with Product Development Issues Using Cellular Particle Swarm optimization (CPSO) Technique:
Vikas Kumar and F.T.S. Chan.
5. Genetic Algorithms with Chromosome Differentiation (GACD) Based Approach for Process Plan Selection Problems:
Nishikant Mishra and Vikas Kumar.
6. Operation Allocation in Flexible Manufacturing System Using Immune Algorithm:
Mayank K. Pandey.
7. Tool Selection in FMS a Hybrid SA-TABU Algorithm Based Approach:
Nitesh Khilwani, J. A. Harding and Nishikant Mishra.
8. Integrating AGVs and Production Planning with Memetic Particle Swarm Optimization:
Sri Krishna Kumar, M K Tiwari and J Harding.
9. Simulation-based Aircraft Assembly Planning Using a Self-Guided Ant Colony Algorithm:
Sai Srinivas Nageshwaraniyer, Nurcin Celik, Young-Jun Son and Roberto Lu.
10. Applications of Evolutionary Computing to Additive Manufacturing:
Candice Majewski.
11. Multiple Fault Diagnosis Using Psycho-Clonal Algorithms:
Nagesh Shukla and Prakash.
12. Platform Formation Under Stochastic Demand:
D. Ben-Arieh and A.M. Choubey.
13. A Hybrid Particle Swarm and Ant Colony Optimizer for Multi-attribute Partnership Selection in Virtual Enterprises:
S.H. Niu, S.K. Ong and A.Y.C. Nee.
Index.
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Preface.
1. Production Planning Using Genetic Algorithm:
S. K. Kumar and M. K. Tiwari.
2. Process Planning Through Ant Colony Optimization:
Puneet Bhardwaj and M. K.Tiwari.
3. Introducing a Hybrid Genetic Algorithm for Integration of Set Up and Process Planning:
S.H. Chung and F.T.S. Chan.
4. Design for Supply Chain with Product Development Issues Using Cellular Particle Swarm optimization (CPSO) Technique:
Vikas Kumar and F.T.S. Chan.
5. Genetic Algorithms with Chromosome Differentiation (GACD) Based Approach for Process Plan Selection Problems:
Nishikant Mishra and Vikas Kumar.
6. Operation Allocation in Flexible Manufacturing System Using Immune Algorithm:
Mayank K. Pandey.
7. Tool Selection in FMS a Hybrid SA-TABU Algorithm Based Approach:
Nitesh Khilwani, J. A. Harding and Nishikant Mishra.
8. Integrating AGVs and Production Planning with Memetic Particle Swarm Optimization:
Sri Krishna Kumar, M K Tiwari and J Harding.
9. Simulation-based Aircraft Assembly Planning Using a Self-Guided Ant Colony Algorithm:
Sai Srinivas Nageshwaraniyer, Nurcin Celik, Young-Jun Son and Roberto Lu.
10. Applications of Evolutionary Computing to Additive Manufacturing:
Candice Majewski.
11. Multiple Fault Diagnosis Using Psycho-Clonal Algorithms:
Nagesh Shukla and Prakash.
12. Platform Formation Under Stochastic Demand:
D. Ben-Arieh and A.M. Choubey.
13. A Hybrid Particle Swarm and Ant Colony Optimizer for Multi-attribute Partnership Selection in Virtual Enterprises:
S.H. Niu, S.K. Ong and A.Y.C. Nee.
Index.
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BISAC SUBJECT HEADINGS
TEC 020000: Technology & Engineering/ Manufacturing
COM032000: Computers/ Information Technology
BUS 087000: Business & Economics/ Production & Operations Management
BIC CODES
UY: Computer Science
KND: Manufacturing Industries
TGP: Production Engineering
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