Skip to main content

Optimization Models to Support Decision-Making in Collaborative Networks: A Review

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Management and Industrial Engineering ((LNMIE))

Abstract

Enterprises, especially SMEs, are increasingly aware of belonging to Collaborative Networks (CN), due to the competitive advantages associated to deal with markets globalization and turbulence. The participation in CN involves enterprises to perform collaborative planning along all the processes established with the CN partners. Nevertheless, the access of SMEs to optimisation tools, for dealing with collaborative planning, is currently limited. To solve this concern, novel optimisation approaches have to be designed in order to improve the integrated planning in CN. In order to deal with this problem, this paper proposes a baseline to identify current enterprise needs and literature solutions in the replenishment, production and delivery collaborative planning, as a part of the H2020 Cloud Collaborative Manufacturing Networks (C2NET) research project. The main gaps found between the literature reviewed and the enterprises’ needs are presented and discussed.

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

References

  • Alemany MME, Boj JJ, Mula J, Lario FC (2010) Mathematical programming model for centralised master planning in ceramic tile supply chains. Int J Prod Res 48(17):5053–5074

    Article  MATH  Google Scholar 

  • Billington PJ, McClain JO, Thomas LJ (1983) Mathematical programming approaches to capacity-constrained MRP systems: review, formulation and problem reduction. Manage Sci 29(10):1126–1141

    Article  MATH  Google Scholar 

  • Chen CL, Lee WC (2004) Multi-objective optimization of multi-echelon supply chain networks with uncertain product demand and prices. Comput Chem Eng 28:1131–1144

    Article  Google Scholar 

  • Clark AR (2003) Optimization approximations for capacity constrained material requirements planning. Int J Prod Econ 84(2):115–131

    Article  Google Scholar 

  • Escudero LF (1994) CMIT, capacitated multi-level implosion tool. Eur J Oper Res 76(3):511–528

    Article  MATH  Google Scholar 

  • Franz C, Hällgren EC, Koberstein A (2014) Resequencing orders on mixed-model assembly lines: heuristic approaches to minimise the number of overload situations. Int J Prod Res 52(19):5823–5840

    Article  Google Scholar 

  • Gansterer M (2015). Aggregate planning and forecasting in make-to-order production systems. Int J Prod Econ

    Google Scholar 

  • Giglio D, Minciardi R (2003) Modelling and optimization of multi-site production systems in supply chain networks. In: Proceedings IEEE international conference on systems, man and cybernetics, vol. 3, pp 2678–2683

    Google Scholar 

  • Gupta D, Magnusson T (2005) The capacitated lot-sizing and scheduling problem with sequence-dependent setup costs and setup times. Comput Oper Res 32(4):727–747

    Article  MathSciNet  MATH  Google Scholar 

  • Hernández JE, Mula J, Poler R, Lyons AC (2014) Collaborative planning in multi-tier supply chains supported by a negotiation-based mechanism and multi-agent system. Group Decis Negot 23(2):235–269

    Article  Google Scholar 

  • Karimi IA, McDonald CM (1997) Planning and scheduling of parallel semicontinuous processes. 2. Short-term scheduling. Ind Eng Chem Res 36(7):2701–2714

    Article  Google Scholar 

  • Lim SJ, Jeong KS, Kim MW, Park (2005) A simulation approach for production-distribution planning with consideration given to replenishment policies. Int J Adv Manuf Technol 27, pp 593–603

    Google Scholar 

  • McDonald CM, Karimi IA (1997) Planning and scheduling of parallel semicontinuous processes. 1. Production planning. Ind Eng Chem Res 36(7):2691–2700

    Article  Google Scholar 

  • Mula J, Poler R, Garcia-Sabater JP, Lario FC (2006) Models for production planning under uncertainty: a review

    Google Scholar 

  • Mula J, Peidro D, Poler R (2010) The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand. Int J Prod Econ 128:136–143

    Article  MATH  Google Scholar 

  • Noori S, Feylizadeh MR, Bagherpour M, Zorriassatine F, Parkin RM (2008) Optimization of material requirement planning by fuzzy multi-objective linear programming. Proce Inst Mech Eng—Part B—Eng Manuf 222(7):887–900

    Google Scholar 

  • Rota K, Thierry C, Bel G (1997) Capacity-constrained MRP system: a mathematical programming model integrating firm orders, forecasts and suppliers. Universite Toulouse II Le Mirail, Departament d’Automatique

    Google Scholar 

  • Sabri EH, Beamon BM (2000) A multi-objective approach to simultaneous strategic and operational planning in supply chain design. Omega 28(5):581–598

    Article  Google Scholar 

  • Supply Chain Council (2012) Supply chain operations reference model (SCOR). Supply chain operations management. Retrieved from: http://www.apics.org/sites/apics-supply-chain-council/frameworks/scor

  • Yenisey MM (2006) A flow-network approach for equilibrium of material requirements planning. Int J Prod Econ 102(2):317–332

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgements

The research leading to these results is in the frame of the “Cloud Collaborative Manufacturing Networks” (C2NET) project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 636,909.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Beatriz Andres .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Andres, B., Poler, R., Saari, L., Arana, J., Benaches, JV., Salazar, J. (2018). Optimization Models to Support Decision-Making in Collaborative Networks: A Review. In: Viles, E., Ormazábal, M., Lleó, A. (eds) Closing the Gap Between Practice and Research in Industrial Engineering. Lecture Notes in Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-58409-6_28

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-58409-6_28

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-58408-9

  • Online ISBN: 978-3-319-58409-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics