Constraints

, Volume 22, Issue 4, pp 530–547 | Cite as

Cumulative scheduling with variable task profiles and concave piecewise linear processing rate functions

Article
Part of the following topical collections:
  1. Topical Collection on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming

Abstract

We consider a cumulative scheduling problem where a task duration and resource consumption are not fixed. The consumption profile of the task, which can vary continuously over time, is a decision variable of the problem to be determined and a task is completed as soon as the integration over its time window of a non-decreasing and continuous processing rate function of the consumption profile has reached a predefined amount of energy. The goal is to find a feasible schedule, which is an NP-hard problem. For the case where functions are concave and piecewise linear, we present two propagation algorithms. The first one is the adaptation to concave functions of the variant of the energetic reasoning previously established for linear functions. Furthermore, a full characterization of the relevant intervals for time-window adjustments is provided. The second algorithm combines a flow-based checker with time-bound adjustments derived from the time-table disjunctive reasoning for the cumulative constraint. Complementarity of the algorithms is assessed via their integration in a hybrid branch-and-bound and computational experiments on small-size instances.

Keywords

Continuous scheduling Continuous resources Concave piecewise linear functions Energy constraints Energetic reasoning 

Notes

Acknowledgments

The authors thank José Verschae for enlightening discussions. This study was partially supported by project “Energy-Efficient and Robust approaches for the Scheduling of Production, Services and Urban Transport”, ECOS/CONICYT, N C13E04.

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Margaux Nattaf
    • 1
  • Christian Artigues
    • 1
  • Pierre Lopez
    • 1
  1. 1.LAAS-CNRSUniversité de Toulouse, CNRS, INSAToulouseFrance

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