Effective Methods for Integrated Process Planning and Scheduling

1. Front Matter

   Pages i-xvi

   PDF

2. Introduction for Integrated Process Planning and Scheduling

   • Xinyu Li, Liang Gao

   Pages 1-15

3. Review for Flexible Job Shop Scheduling

   • Xinyu Li, Liang Gao

   Pages 17-45

4. Review for Integrated Process Planning and Scheduling

   • Xinyu Li, Liang Gao

   Pages 47-59

5. Improved Genetic Programming for Process Planning

   • Xinyu Li, Liang Gao

   Pages 61-79

6. An Efficient Modified Particle Swarm Optimization Algorithm for Process Planning

   • Xinyu Li, Liang Gao

   Pages 81-106

7. A Hybrid Algorithm for Job Shop Scheduling Problem

   • Xinyu Li, Liang Gao

   Pages 107-131

8. An Effective Genetic Algorithm for FJSP

   • Xinyu Li, Liang Gao

   Pages 133-155

9. An Effective Collaborative Evolutionary Algorithm for FJSP

   • Xinyu Li, Liang Gao

   Pages 157-165

10. Mathematical Modeling and Evolutionary Algorithm-Based Approach for IPPS

    • Xinyu Li, Liang Gao

    Pages 167-189

11. An Agent-Based Approach for IPPS

    • Xinyu Li, Liang Gao

    Pages 191-208

12. A Modified Genetic Algorithm Based Approach for IPPS

    • Xinyu Li, Liang Gao

    Pages 209-233

13. An Effective Hybrid Algorithm for IPPS

    • Xinyu Li, Liang Gao

    Pages 235-249

14. An Effective Hybrid Particle Swarm Optimization Algorithm for Multi-objective FJSP

    • Xinyu Li, Liang Gao

    Pages 251-277

15. A Multi-objective GA Based on Immune and Entropy Principle for FJSP

    • Xinyu Li, Liang Gao

    Pages 279-300

16. An Effective Genetic Algorithm for Multi-objective IPPS with Various Flexibilities in Process Planning

    • Xinyu Li, Liang Gao

    Pages 301-322

17. Application of Game Theory-Based Hybrid Algorithm for Multi-objective IPPS

    • Xinyu Li, Liang Gao

    Pages 323-343

18. A Hybrid Intelligent Algorithm and Rescheduling Technique for Dynamic JSP

    • Xinyu Li, Liang Gao

    Pages 345-375

19. A Hybrid Genetic Algorithm and Tabu Search for Multi-objective Dynamic JSP

    • Xinyu Li, Liang Gao

    Pages 377-403

20. GEP-Based Reactive Scheduling Policies for Dynamic FJSP with Job Release Dates

    • Xinyu Li, Liang Gao

    Pages 405-428

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.

• Dynamic Scheduling
• IPPS Reference
• Integrated Process Planning and Scheduling
• Intelligent Optimization Algorithms
• Multi-objective Optimization
• Production Planning and Scheduling

• School of Mechanical Science and Engineering, HUST, State Key Laboratory of Digital Manufacturing and Equipment Technology, Wuhan, China

  Xinyu Li, Liang Gao

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 wona 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.

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