Effective Methods for Integrated Process Planning and Scheduling (eBook, PDF) - Li, Xinyu; Gao, Liang
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This book summarizes a series of research work on integrated process planning and scheduling (IPPS) done by the authors, focusing on discussing the properties, novel solution methods and applications of process planning, scheduling and IPPS problems under different machining environments. It is a valuable reference resource for teachers, students and researchers working in the fields of engineering, management science and other related disciplines.…mehr

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Produktbeschreibung
This book summarizes a series of research work on integrated process planning and scheduling (IPPS) done by the authors, focusing on discussing the properties, novel solution methods and applications of process planning, scheduling and IPPS problems under different machining environments. It is a valuable reference resource for teachers, students and researchers working in the fields of engineering, management science and other related disciplines.

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  • Produktdetails
  • Verlag: Springer-Verlag GmbH
  • Seitenzahl: 462
  • Erscheinungstermin: 3. Juni 2020
  • Englisch
  • ISBN-13: 9783662553053
  • Artikelnr.: 59574527
Autorenporträt
Xinyu Li is an Associate Professor at the School of Mechanical Science and Engineering, Huazhong University of Science and Technology, China. He is a member of the State Key Laboratory of Digital Manufacturing Equipment and Technology (DMET) and a member of the Operations Research Society of China, Artificial Intelligence Society of Hubei, Operations Research Society of Hubei and Mechanical Engineering Society of Hubei. He was the guest co-editor of the special issues of International Journal of Advancements in Computing Technology on "Particle Swarm Optimization and Applications" in 2011 and the International Journal of Advanced Manufacturing Technology on "Process Planning and Production Scheduling in Sustainable Manufacturing" in 2012. His main research areas are integration of process planning and scheduling, process parameter optimization, approximation algorithms and flexible job shop scheduling. He has published 65 papers in international journals and at conferences. He has won a number of awards, including the "Science & Technology Award for Youth" from the Operations Research Society of China, and a Ministry of Education Natural Science Award in 2013. He was also nominated for "Excellent Dissertation Award " by the Ministry of Education of China.
Liang Gao is a Professor at the School of Mechanical Science and Engineering, Huazhong University of Science and Technology. He is an Associate Director of the State Key Laboratory of Digital Manufacturing Equipment and Technology (DMET). He is a member of the Operations Research Society of China, Artificial Intelligence Society of Hubei, Operations Research Society of Hubei and Mechanical Engineering Society of Hubei. He was also the guest co-editor of the special issues of International Journal of Advancements in Computing Technology on "Particle Swarm Optimization and Applications" in 2011 and International Journal of Advanced Manufacturing Technology on "Process Planning
and Production Scheduling in Sustainable Manufacturing" in 2012. He was a referee for the International Journal of Production Research, International Journal of Computer Integrated Manufacturing and other related international journals. His main research areas are the modern optimization method and its applications in mechanical design and manufacturing. Over the last 5 years, he has published 2 books and 53 papers in respected journals. He has received a number of awards, including the Ministry of Education Natural Science Award first prize in 2013 and the Chinese Mechanical Engineering Society Youth Science and Technology Achievement Award in 2013. He was selected for the Program for New Century Excellent Talents in University by the Ministry of Education in 2008.
Inhaltsangabe
Problem Review.- Methods for single objective problem.- Methods for the Multi-objectives problem.- Dynamic scheduling.- Application.