Skip to main content

Event Management for Uncertainties in Collaborative Production Scheduling and Transportation Planning: A Review

  • Conference paper
  • First Online:
  • 2230 Accesses

Part of the book series: Lecture Notes in Logistics ((LNLO))

Abstract

This paper presents a review of using event management to deal with the uncertainties in production scheduling and transportation planning processes at the operational level. Moreover, it argues the importance of considering uncertainties and the application of event management in a collaborative production and transportation planning process at the operational level.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    The decision to delay some manufacturing activities like assembly, labeling or packaging.

  2. 2.

    The set of active schedules is a subset of feasible schedules for a scheduling problem. Giffler and Tompson (1960 )proved that at least one optimal schedule is active schedule. Their work also presents a heuristics, which can generate all possible active schedules. Dispatching rules are usually used to lead the search directions in this heuristics to generate active schedules.

References

  • Bonfill A, Espuna A, Puigjaner L (2008) Decision support framework for coordinated production and transport scheduling in SCM. Comput Chem Eng 32:1206–1224

    Article  Google Scholar 

  • Chen CC, Yih Y (1996) Identifying attributes for knowledge-based development in dynamic scheduling environments. Int J Prod Res 34:1739–1755

    Article  MATH  Google Scholar 

  • Christopher M, Mena C, Khan O, Yurt O (2011) Approaches to managing global sourcing risk. Supply Chain Manag: Int J 16(2):67–81

    Article  Google Scholar 

  • Fortes J (2007) Green supply chain management: a literature review. Otago Manag Graduate Rev 7:51–62

    Google Scholar 

  • Giffler B, Tompson GL (1960) Algorithms for solving production-scheduling problems. Oper Res 8:487–503

    Article  MATH  Google Scholar 

  • Khan O, Burnes B (2007) Risk and supply chain management: creating a research agenda. Int J Logistic Manag 18(2):197–216

    Article  Google Scholar 

  • Larsen ER, Morecroft JDW, Thomsen JS (1999) Theory and methodology: complex behavior in a production-distribution model. E J Oper Res 119:61–74

    Article  MATH  Google Scholar 

  • Li L, Schulze L (2011) Uncertainty in logistics network design: a review. In: Proceedings of the international multi conference of engineers and computer scientist II, IMECS 2011

    Google Scholar 

  • Manuj I, Mentzer JT (2008) Global supply chain risk management strategies. Int J Phys Distrib Logistics Manag 38(3):192–223

    Article  Google Scholar 

  • Otto A (2003) Supply chain event management: three perspectives. Int J Logistics Manag 14(2):1–13

    Article  Google Scholar 

  • Pfund ME, Mason SJ, Fowler JW (2006) Semiconductor manufacturing scheduling and dispatching. In: Herrmann JW (ed) Handbook of production scheduling. Springer, New York

    Google Scholar 

  • Priore P, De La Fuente D, Gomez A, Puente J (2001) A review of machine learning in dynamic scheduling of flexible manufacturing systems. Artif Intell Eng Des Anal Manuf 15:251–263

    MATH  Google Scholar 

  • Ritchie B, Brindley C (2007a) Supply chain risk management and performance: a guiding framework for future development. Int J Oper Prod Manag 27(3):303–322

    Article  Google Scholar 

  • Ritchie B, Brindley C (2007b) An emergent framework for supply chain risk management and performance measurement. J Oper Res Soc 58(11):1398–1412

    Article  MATH  Google Scholar 

  • Rodrigue VS, Stantche D, Potte A, Naim M, Whitein A (2007) Establishing a transport operation focused uncertainty model for the supply chain. In: 14th international annual Euroma conference

    Google Scholar 

  • Sanchez-Rodrigues V, Potter A, Naim M (2010a) Evaluating the causes of uncertainty in logistics operations. Int J Logistics Manag 21(1):45–64

    Article  Google Scholar 

  • Sanchez-Rodrigues V, Potter A, Naim M (2010b) The impact of logistics uncertainty on sustainable transport operations. Int J Phys Distrib Logistics Manag 40(1):61–83

    Article  Google Scholar 

  • Sanchez-Rodrigues V, Stantchev D, Potter A, Naim M, Whiteing A (2008) Establishing a transport focused uncertainty model for the supply chain. Int J Phys Distrib Logistics Manag 38(5):388–411

    Article  Google Scholar 

  • Stank TP, Dittmann JP, Autry CW (2011) The new supply chain agenda: a synopsis and directions for future research. Int J Phys Distrib Logistics Manag 41(10):1–25

    Google Scholar 

  • Scholz-Reiter B, Novaes AGN, Makuschewitz T, Frazzon EM (2011) Dynamic scheduling of production and inter-facilities logistic systems. Dynamics in logistics. Springer, Berlin

    Google Scholar 

  • Tan Y, Aufenanger M (2011) A real-time rescheduling heuristic using decentralized knowledge-based decisions for flexible flow shops with unrelated parallel machines. In: Proceedings of the 9th IEEE international conference on industrial informatics. pp. 431–436

    Google Scholar 

  • Tang CS (2006) Perspectives in supply chain risk management. Int J Prod Econ 103:451–488

    Article  Google Scholar 

  • Vieira GE, Herrmann JW, Lin E (2003) Rescheduling manufacturing systems: a framework of strategies, policies, and methods. J Sched 6:39–62

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgments

This research was supported by the International Graduate School for Dynamics in Logistics (IGS) at the University of Bremen, by Capes as part of the Brazilian-German Collaborative Research Initiative on Manufacturing Technology (BRAGECRIM) and by Deutscher Akademischer Austausch Dienst (DAAD) and the Egyptian Government under Grant GERLS 2010.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yi Tan .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Scholz-Reiter, B., Tan, Y., El-Berishy, N., Santos, J.B.S. (2013). Event Management for Uncertainties in Collaborative Production Scheduling and Transportation Planning: A Review. In: Kreowski, HJ., Scholz-Reiter, B., Thoben, KD. (eds) Dynamics in Logistics. Lecture Notes in Logistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35966-8_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-35966-8_16

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35965-1

  • Online ISBN: 978-3-642-35966-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics