Abstract
Motivated by the necessity to model the energy loss of energy storage devices, a Proportional Constraint is introduced in finite integer domain Constraint Programming. Therefore rounding is used within its definition. For practical applications in finite domain Constraint Programming, pruning rules are presented and their correctness is proven. Further, it is shown by examples that the number of iterations necessary to reach a fixed-point while pruning depends on the considered constraint instances. However, fixed-point iteration always results in the strongest notion of bounds consistency. Furthermore, an alternative modeling of the Proportional Constraint is presented. The run-times of the implementations of both alternatives are compared showing that the implementation of the Proportional Constraint on the basis of the presented pruning rules performs always better on sample problem classes.
The presented work is funded by the German Federal Ministry for Economic Affairs and Energy within the project “WaveSave” (BMWi, funding number 03ET1312A).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
The formal proof by induction is left to the interested reader.
- 3.
Many thanks to the anonymous reviewer who suggested this approach.
References
Bosman, M., Bakker, V., Molderink, A., Hurink, J., Smit, G.: Planning the production of a fleet of domestic combined heat and power generators. Eur. J. Oper. Res. 216, 140–151 (2012)
Bozchalui, M.C., Sharma, R.: Optimal operation of commercial building microgrids using multi-objective optimization to achieve emissions and efficiency targets. In: 2012 IEEE Power and Energy Society General Meeting, pp. 1–8. IEEE (2012)
Brahman, F., Honarmand, M., Jadid, S.: Optimal electrical and thermal energy management of a residential energy hub, integrating demand response and energy storage system. Energy Build. 90, 65–75 (2015)
Baptiste, P., Pape, C.L., Nuijten, W.: Constraint-Based Scheduling - Applying Constraint Programming to Scheduling Problems. Springer, Boston (2001). https://doi.org/10.1007/978-1-4615-1479-4
Schulte, C., Stuckey, P.J.: When do bounds and domain propagation lead to the same search space? ACM Trans. Program. Lang. Syst. (TOPLAS) 27(3), 388–425 (2005)
Wolf, A.: firstCS - new aspects on combining constraint programming with object-orientation in Java. KI - Künstliche Intelligenz 26(1), 55–60 (2012)
Apt, K.R.: From chaotic iteration to constraint propagation. In: Degano, P., Gorrieri, R., Marchetti-Spaccamela, A. (eds.) ICALP 1997. LNCS, vol. 1256, pp. 36–55. Springer, Heidelberg (1997). https://doi.org/10.1007/3-540-63165-8_163
Choi, C.W., Harvey, W., Lee, J.H.M., Stuckey, P.J.: Finite domain bounds consistency revisited. In: Sattar, A., Kang, B. (eds.) AI 2006. LNCS (LNAI), vol. 4304, pp. 49–58. Springer, Heidelberg (2006). https://doi.org/10.1007/11941439_9
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Wolf, A. (2018). The Proportional Constraint and Its Pruning. In: Seipel, D., Hanus, M., Abreu, S. (eds) Declarative Programming and Knowledge Management. WFLP WLP INAP 2017 2017 2017. Lecture Notes in Computer Science(), vol 10997. Springer, Cham. https://doi.org/10.1007/978-3-030-00801-7_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-00801-7_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-00800-0
Online ISBN: 978-3-030-00801-7
eBook Packages: Computer ScienceComputer Science (R0)