Skip to main content

Bridging the Gap between Rich Supply Chain Problems and the Effective Application of Metaheuristics through Ontology-Based Modeling

  • Conference paper
  • 1286 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8111))

Abstract

Supply chains (SC) are exposed to dynamic markets and enlarged network structures. This induces abundant decision complexity and the need to frequently adapt decisions. Metaheuristics are most suitable for rich SC optimization problems. However, effectiveness and adaptability of these approaches are impaired through extensive modeling efforts and intricate data representation issues. Therefore we propose using ontological modeling to mitigate these disadvantages.

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   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Benyoucef, L., Jain, V.: Editorial note for the special issue on ‘Artificial Intelligence Techniques for Supply Chain Management’. Engineering Applications of Artificial Intelligence 22(6), 829–831 (2009)

    Article  Google Scholar 

  2. Mirzapour Al-e-hashem, S.M.J., Malekly, H., Aryanezhad, M.B.: A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty. International Journal of Production Economics 134(1), 28–42 (2011)

    Article  Google Scholar 

  3. Schmid, V., Doerner, K.F., Laporte, G.: Rich routing problems arising in supply chain management. European Journal of OR 224(3), 435–448 (2013)

    MathSciNet  Google Scholar 

  4. Affenzeller, M., et al.: Genetic Algrothims and Genetic Programming - Modern Concepts and Practical Applications. CRC Taylor & Francis Group (2009)

    Google Scholar 

  5. Arthofer, K., et al.: Servicing Individual Product Variants within Value Chains with an Ontology. In: Modelling Value. Selected Papers of the 1st International Conference on Value Chain Management, pp. 333–354 (2012)

    Google Scholar 

  6. Gruber, T.R.: A translation approach to portable ontology specifications. Knowledge Acquisition 5(2), 199–220 (1993)

    Article  Google Scholar 

  7. Williamson, O.E.: The economic institutions of capitalism. Firms, markets, relational contracting. Free Press, Collier Macmillan, New York, London (1985)

    Google Scholar 

  8. Bendoly, E., et al.: Bodies of Knowledge for Research in Behavioral Operations. Production & Operations Management 19(4), 434–452 (2010)

    Article  Google Scholar 

  9. Studer, R., Fensel, D.: Knowledge engineering: Principles and methods. Data & Knowledge Engineering 25(1-2), 161–197 (1998)

    Article  MATH  Google Scholar 

  10. Grubic, T., Fan, I.-S.: Supply Chain Ontology: Review, analysis and synthesis. Computers in Industry 61(8), 776–786 (2010)

    Article  Google Scholar 

  11. Swartout, B., et al.: Toward Distributed Use of Large-Scale Ontologies. In: AAAI 1997 Spring Symposium on Ontological Engineering, Stanford University, CA, USA, pp. 138–148 (1997)

    Google Scholar 

  12. Hillier, F.S., Lieberman, G.: Introduction to Operations Research. McGraw-Hill International Edition, New York (2010)

    Google Scholar 

  13. Ahlert, K.-H., Corsten, H., Gössinger, R.: Capacity management in order-driven production networks - A flexibility-oriented approach to determine the size of a network capacity pool. Int. Journal of Production Economics 118(2), 430–441 (2009)

    Article  Google Scholar 

  14. Lee, J., et al.: Design of product ontology architecture for collaborative enterprises. Expert Systems with Applications 36(2), 2300–2309 (2009)

    Article  Google Scholar 

  15. Brock, D.L., et al.: An Introduction to semantic modeling for logistical systems. Journal of Business Logistics 26(2), 97–117 (2005)

    Article  Google Scholar 

  16. Chi, Y.-L.: Rule-based ontological knowledge base for monitoring partners across supply networks. Expert Systems with Applications 37(2), 1400–1407 (2010)

    Article  Google Scholar 

  17. Horridge, M., et al.: A Practical Guide to Building OWL Ontologies using the Protege-OWL Plugin and CO-ODE Tools Edition 1.0 (2004)

    Google Scholar 

  18. Lacy, L.W.: Owl: Representing Information Using the Web Ontology Language. Trafford Publishing, Victoria (2005)

    Google Scholar 

  19. Prud’hommeaux, E., Seaborne, A.: SPARQL Query Language for RDF (2008)

    Google Scholar 

  20. Latha Shankar, B., et al.: Location and allocation decisions for multi-echelon supply chain network - A multi-objective evolutionary approach. Expert Systems with Applications 40(2), 551–562 (2013)

    Article  Google Scholar 

  21. Rotter, S.: Supply Chain Network Design - A Facility Location and Allocation Model for Biomass-based Energy Carrier Production in Upper Austria (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Engelhardt-Nowitzki, C., Rotter, S., Affenzeller, M. (2013). Bridging the Gap between Rich Supply Chain Problems and the Effective Application of Metaheuristics through Ontology-Based Modeling. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory - EUROCAST 2013. EUROCAST 2013. Lecture Notes in Computer Science, vol 8111. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53856-8_38

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-53856-8_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53855-1

  • Online ISBN: 978-3-642-53856-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics