Skip to main content

The TaskIntersection Constraint

  • Conference paper
  • First Online:
  • 1307 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9676))

Abstract

Given a sequence of tasks \(\mathcal {T}\) subject to precedence constraints between adjacent tasks, and given a set of fixed intervals \(\mathcal {I}\), the TaskIntersection \((\mathcal {T},\mathcal {I},o, inter )\) constraint restricts the overall intersection of the tasks of \(\mathcal {T}\) with the fixed intervals of \(\mathcal {I}\) to be greater than or equal (\(o=\) ‘\(\ge \)’) or less than or equal (\(o=\) ‘\(\le \)’) to a given limit \( inter \). We provide a bound(\(\mathbb {Z}\))-consistent cost filtering algorithm wrt the starts and the ends of the tasks for the TaskIntersection constraint and evaluate the constraint on the video summarisation problem.

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 EPUB and 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

References

  1. Aggoun, A., Beldiceanu, N.: Extending CHIP in order to solve complex scheduling and placement problems. Math. Comput. Model. 17(7), 57–73 (1993)

    Article  Google Scholar 

  2. Allen, J.F.: Maintaining knowledge about temporal intervals. Commun. ACM 26(11), 832–843 (1983)

    Article  MATH  Google Scholar 

  3. Baptiste, P., Le Pape, C., Nuijten, W.: Constraint-Based Scheduling: Applying Constraint Programming to Scheduling Problems. International Series in Operations Research & Management Science, vol. 39. Springer Science & Business Media, Berlin (2012)

    MATH  Google Scholar 

  4. Berrani, S.A., Boukadida, H., Gros, P.: Constraint satisfaction programming for video summarization. In: 2013 IEEE International Symposium on Multimedia (ISM), pp. 195–202. IEEE (2013)

    Google Scholar 

  5. Bessiére, C.: Constraint propagation. Handbook of constraint programming, pp. 29–83 (2006). Chap. 3

    Google Scholar 

  6. Boukadida, H., Berrani, S.-A., Gros, P.: A novel modeling for video summarization using constraint satisfaction programming. In: Bebis, G., et al. (eds.) ISVC 2014, Part II. LNCS, vol. 8888, pp. 208–219. Springer, Heidelberg (2014)

    Google Scholar 

  7. Derrien, A., Fages, J.-G., Petit, T., Prudhomme, C.: A global constraint for a tractable class of temporal optimization problems. In: Pesant, G. (ed.) CP 2015. LNCS, vol. 9255, pp. 105–120. Springer, Heidelberg (2015)

    Google Scholar 

  8. Ekin, A., Mehrotra, R., et al.: Automatic soccer video analysis and summarization. IEEE Trans. Image Process. 12(7), 796–807 (2003)

    Article  Google Scholar 

  9. Fages, J.G., Prud’homme, C.: A free and open-source Java library for constraint programming (2015). http://choco.emn.fr/

  10. Kumar, T.S., Cirillo, M., Koenig, S.: Simple temporal problems with taboo regions. In: AAAI. Citeseer (2013)

    Google Scholar 

  11. Madi Wamba, G.: Random generated instances of the taskintersection problem (2015). https://www.dropbox.com/sh/uwvn86rx7mxebty/AADyUAdnEWdOkmC8Xkcyjg3Ua?dl=0

  12. Simonis, H., Hadzic, T.: A family of resource constraints for energy cost aware scheduling. In: Third International Workshop on Constraint Reasoning and Optimization for Computational Sustainability, St. Andrews, Scotland, UK, September 2010

    Google Scholar 

  13. Simonis, H., Hadzic, T.: A resource cost aware cumulative. In: Larrosa, J., O’Sullivan, B. (eds.) CSCLP 2009. LNCS, vol. 6384, pp. 76–89. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  14. Sourd, F.: Optimal timing of a sequence of tasks with general completion costs. Eur. J. Oper. Res. 165(1), 82–96 (2005)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgement

This work has received a French state support granted to the CominLabs excellence laboratory and managed by the National Research Agency in the “Investing for the Future” program under reference Nb. ANR-10-LABX-07-01. We would like to thank the reviewers for their comments that help improve the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gilles Madi Wamba .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Madi Wamba, G., Beldiceanu, N. (2016). The TaskIntersection Constraint. In: Quimper, CG. (eds) Integration of AI and OR Techniques in Constraint Programming. CPAIOR 2016. Lecture Notes in Computer Science(), vol 9676. Springer, Cham. https://doi.org/10.1007/978-3-319-33954-2_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-33954-2_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33953-5

  • Online ISBN: 978-3-319-33954-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics