Skip to main content

Hierarchical Type-2 Fuzzy Logic Based Real Time Dynamic Operational Planning System

  • Conference paper
  • First Online:
Research and Development in Intelligent Systems XXXI (SGAI 2014)

Abstract

Operational resource planning is critical for successful operations in service-based organizations as it underpins the process of utilizing resources to achieve a higher quality of service whilst lowering operational costs. The majority of service-based organizations use static operational planning. In recent years these, organizations have made attempts to switch to dynamic operational planners with the view of generating real-time operational plans. This paper proposes a hierarchical type-2 fuzzy logic based operational planner that can work in dynamic environments and can maintain operational plans in real-time. The proposed system outperformed ordinary heuristic-based systems and task dispatchers.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Owusu, G., Kern, M., Voudouris, C., Garyfalos, A., Anim-Ansah, G., Virginas, B.: On optimising resource planning in BT plc with FOS. In: International Conference on Service Systems and Service Management, Troyes, pp. 541–546 (2006)

    Google Scholar 

  2. Juedes, D., Drews, F., Welch, L., Fleeman, D.: Heuristic resource allocation algorithms for maximizing allowable workload in dynamic distributed real-time systems. In: Proceedings of the 2004 Symposium on Parallel and Distributed Processing (2004)

    Google Scholar 

  3. Aber, E., Drews, F., Gu, D., Juedes, D., Lenharth, A.: Experimental comparison of heuristic and optimal resource allocation algorithms for maximizing allowable workload in dynamic, distributed real-time systems. In: Proceedings of the 22nd Brazilian Symposium on Computer Networks-6th Brazilian Workshop on Real-Time Systems (WTR 2004) (2004)

    Google Scholar 

  4. Almeida, A., Aknine, S., Briot, J.: Dynamic resource allocation heuristics for providing fault tolerance in multi-agent systems. In: Proceedings of the 2008 ACM Symposium on Applied Computing, pp. 66–70 (2008)

    Google Scholar 

  5. Hagras, H.: A Hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots. IEEE Trans. Fuzzy Syst. 12(4), 524–539 (2004)

    Article  Google Scholar 

  6. Wang, D., Zeng, X., Keane, J.: A survey of hierarchical fuzzy systems. Int. J. Comput. Cogn. 4(1), 18–29 (2006)

    Google Scholar 

  7. Mohamed, A., Hagras, H., Liret, A., Shakya, S., Owusu, G.: A genetic interval type-2 fuzzy logic based approach for operational resource planning. In: IEEE International Conference on Fuzzy Systems, pp. 1–8 (2013)

    Google Scholar 

  8. Erol, O., Eksin, I.: A new optimization method: Big Bang-Big Crunch. Adv. Eng. Soft. 37(2), 106–111 (2006)

    Article  Google Scholar 

  9. Jaradat, G.M., Ayob, M.: Big Bang-Big Crunch optimization algorithm to solve the course timetabling problem. In: Intelligent Systems Design and Applications (ISDA), pp. 1448–1452 (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ahmed Mohamed .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Mohamed, A., Hagras, H., Shakya, S., Liret, A., Dorne, R., Owusu, G. (2014). Hierarchical Type-2 Fuzzy Logic Based Real Time Dynamic Operational Planning System. In: Bramer, M., Petridis, M. (eds) Research and Development in Intelligent Systems XXXI. SGAI 2014. Springer, Cham. https://doi.org/10.1007/978-3-319-12069-0_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-12069-0_19

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12068-3

  • Online ISBN: 978-3-319-12069-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics