Advertisement

A Resource Cost Aware Cumulative

  • Helmut Simonis
  • Tarik Hadzic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6384)

Abstract

We motivate and introduce an extension of the well-known cumulative constraint which deals with time and volume dependent cost of resources. Our research is primarily interested in scheduling problems under time and volume variable electricity costs, but the constraint equally applies to manpower scheduling when hourly rates differ over time and/or extra personnel incur higher hourly rates. We present a number of possible lower bounds on the cost, including a min-cost flow, different LP and MIP models, as well as greedy algorithms, and provide a theoretical and experimental comparison of the different methods.

Keywords

Greedy Algorithm Cost Distribution Cumulative Constraint Random Cost Manpower Schedule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Aggoun, A., Beldiceanu, N.: Extending CHIP in order to solve complex scheduling problems. Journal of Mathematical and Computer Modelling 17(7), 57–73 (1993)CrossRefGoogle Scholar
  2. 2.
    Baptiste, P., Le Pape, C., Nuijten, W.: Constraint-Based Scheduling: Applying Constraint Programming to Scheduling Problems. Kluwer, Dordrecht (2001)CrossRefzbMATHGoogle Scholar
  3. 3.
    Beldiceanu, N., Carlsson, M.: A new multi-resource cumulatives constraint with negative heights. In: Van Hentenryck, P. (ed.) CP 2002. LNCS, vol. 2470, pp. 63–79. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  4. 4.
    Beldiceanu, N., Carlsson, M., Poder, E.: New filtering for the cumulative constraint in the context of non-overlapping rectangles. In: Perron, L., Trick, M.A. (eds.) CPAIOR 2008. LNCS, vol. 5015, pp. 21–35. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  5. 5.
    Beldiceanu, N., Poder, E.: A continuous multi-resources cumulative constraint with positive-negative resource consumption-production. In: Van Hentenryck, P., Wolsey, L.A. (eds.) CPAIOR 2007. LNCS, vol. 4510, pp. 214–228. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  6. 6.
    Hooker, J.: Integrated Methods for Optimization. Springer, New York (2007)zbMATHGoogle Scholar
  7. 7.
    Mercier, L., Van Hentenryck, P.: Edge finding for cumulative scheduling. INFORMS Journal on Computing 20(1), 143–153 (2008)MathSciNetCrossRefzbMATHGoogle Scholar
  8. 8.
    Schutt, A., Feydy, T., Stuckey, P.J., Wallace, M.: Why cumulative decomposition is not as bad as it sounds. In: Gent, I.P. (ed.) CP 2009. LNCS, vol. 5732, pp. 746–761. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  9. 9.
    Simonis, H., Cornelissens, T.: Modelling producer/consumer constraints. In: Montanari, U., Rossi, F. (eds.) CP 1995. LNCS, vol. 976, pp. 449–462. Springer, Heidelberg (1995)CrossRefGoogle Scholar
  10. 10.
    Vilím, P.: Max energy filtering algorithm for discrete cumulative resources. In: van Hoeve, W.-J., Hooker, J.N. (eds.) CPAIOR 2009. LNCS, vol. 5547, pp. 294–308. Springer, Heidelberg (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Helmut Simonis
    • 1
  • Tarik Hadzic
    • 1
  1. 1.Cork Constraint Computation Centre, Department of Computer ScienceUniversity College CorkIreland

Personalised recommendations