Synthesis and Abstraction of Constraint Models for Hierarchical Resource Allocation Problems

Alexander Schiendorfer, Jan-Philipp Steghöfer, Wolfgang Reif

Abstract

Many resource allocation problems are hard to solve even with state-of-the-art constraint optimisation software upon reaching a certain scale. Our approach to deal with this increasing complexity is to employ a hierarchical “regio-central” mechanism. It requires two techniques: (1) the synthesis of several models of agents providing a certain resource into a centrally and efficiently solvable optimisation problem and (2) the creation of an abstracted version of this centralised model that reduces its complexity when passing it on to higher layers. We present algorithms to create such synthesised and abstracted models in a fully automated way and demonstrate empirically that the obtained solutions are comparable to central solutions but scale better in an example taken from energy management.

References

  1. Abouelela, M. and El-Darieby, M. (2012). Multidomain hierarchical resource allocation for grid applications. Journal of Electrical and Computer Engineering, 2012.
  2. Anders, G., Siefert, F., Steghöfer, J.-P., and Reif, W. (2013a). Trust-based scenarios - predicting future agent behavior in open self-organizing systems. In Proc. of the 7th Int. Workshop on Self Organizing Systems (IWSOS) 2013, Palma de Mallorca. Springer Berlin Heidelberg.
  3. Anders, G., Steghöfer, J.-P., Siefert, F., and Reif, W. (2013b). A Trust- and Cooperation-Based Solution of a Dynamic Resource Allocation Problem. In 7th IEEE International Conference on Self-Adaptive and SelfOrganizing Systems (SASO), Philadelphia, PA. IEEE Computer Society, Washington, D.C.
  4. Bar-Noy, A., Bar-Yehuda, R., Freund, A., Naor, J., and Schieber, B. (2001). A Unified Approach to Approximating Resource Allocation and Scheduling. Journal of the ACM (JACM), 48(5):1069-1090.
  5. Boudjadar, A., David, A., Kim, J. H., Larsen, K. G., Mikucionis, M., Nyman, U., and Skou, A. (2013). Hierarchical scheduling framework based on compositional analysis using uppaal. In Proceedings of FACS 2013, Lecture Notes in Computer Science. Springer.
  6. Boyle, P. (2007). Gaussian processes for regression and optimisation. PhD thesis, Victoria University of Wellington.
  7. Bremer, J., Rapp, B., and Sonnenschein, M. (2010). Support vector based encoding of distributed energy resources' feasible load spaces. In Innovative Smart Grid Technologies Conference Europe (ISGT Europe), pages 1-8. IEEE Power Society.
  8. Chevaleyre, Y., Dunne, P. E., Endriss, U., Lang, J., Lemaitre, M., Maudet, N., Padget, J., Phelps, S., Rodríguez-Aguilar, J. A., and Sousa, P. (2006). Issues in multiagent resource allocation. Informatica, 30(1):3 - 31.
  9. Choueiry, B. Y., Faltings, B., and Noubir, G. (1994). Abstraction methods for resource allocation. Technical CPLEX (2013). IBM ILOG CPLEX Optimizer. Online Resource, last accessed December 2013: http:// www-01.ibm.com/software/commerce/optimization/ cplex-optimizer/.
  10. Deutsche Gesellschaft für Sonnenenergie e.V. (2013). Energymap. Online Resource, last accessed December 2013: http://www.energymap.info/.
  11. Frantz, F. (1995). A taxonomy of model abstraction techniques. In Simulation Conference Proceedings, 1995. Winter, pages 1413-1420.
  12. Giunchiglia, F. and Walsh, T. (1992). A theory of abstraction. Artificial Intelligence, 57(2):323-389.
  13. Heuck, K., Dettmann, K.-D., and Schulz, D. (2010). Elektrische Energieversorgung. Vieweg+Teubner. (in German).
  14. Hladik, P.-E., Cambazard, H., Déplanche, A.-M., and Jussien, N. (2008). Solving a real-time allocation problem with constraint programming. Journal of Systems and Software, 81(1):132-149.
  15. Kinnebrew, J. S. and Biswas, G. (2009). Efficient allocation of hierarchically-decomposable tasks in a sensor web contract net. In Proc. of the 2009 IEEE/WIC/ACM Int. Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02, WI-IAT 7809, pages 225-232, Washington, DC, USA. IEEE Computer Society.
  16. Lee, K. and Fishwick, P. A. (1996). A methodology for dynamic model abstraction. SCS Transactions on Simulation, 13(4):217-229.
  17. LEW Verteilnetz GmbH (2013). LEW Netzdaten. Online Resource, last accessed December 2013: http:// www.lew-verteilnetz.de/.
  18. Meseguer, P., Rossi, F., and Schiex, T. (2006). Soft Constraints. In Rossi, F., van Beek, P., and Walsh, T., editors, Handbook of Constraint Programming, chapter 9. Elsevier.
  19. Pelikan, M. and Goldberg, D. E. (2000). Hierarchical problem solving by the bayesian optimization algorithm. In Proc. of the Genetic and Evolutionary Computation Conference 2000, pages 267-274. Morgan Kaufmann.
  20. Ramchurn, S. D., Vytelingum, P., Rogers, A., and Jennings, N. R. (2012). Putting the 'smarts' into the smart grid: a grand challenge for artificial intelligence. Commun. ACM, 55(4):86-97.
  21. Santos, C., Zhu, X., and Crowder, H. (2002). A mathematical optimization approach for resource allocation in large scale data centers. Technical Report HPL-2002- 64, HP Labs.
  22. Schiendorfer, A., Steghöfer, J.-P., Knapp, A., Nafz, F., and Reif, W. (2013). Constraint relationships for soft constraints. In Bramer, M. and Petridis, M., editors, Research and Development in Intelligent Systems XXX. Springer London.
  23. Steghöfer, J.-P., Anders, G., Siefert, F., and Reif, W. (2013a). A system of systems approach to the evolutionary transformation of power management systems. In Proceedings of INFORMATIK 2013 - Workshop on “Smart Grids”, Lecture Notes in Informatics. Bonner Köllen Verlag.
  24. Steghöfer, J.-P., Behrmann, P., Anders, G., Siefert, F., and Reif, W. (2013b). HiSPADA: Self-organising hierarchies for large-scale multi-agent systems. In Proceedings of the IARIA International Conference on Autonomic and Autonomous Systems (ICAS) 2013. IARIA.
  25. Van Zandt, T. (1995). Hierarchical computation of the resource allocation problem. European Economic Review, 39(3-4):700-708.
  26. Vandewalle, P. (2012). Code sharing is associated with research impact in image processing. Computing in Science Engineering, 14(4):42-47.
  27. Yokoo, M., Durfee, E. H., Ishida, T., and Kuwabara, K. (1998). The distributed constraint satisfaction problem: Formalization and algorithms. IEEE Transactions on Knowledge and Data Engineering, 10:673- 685.
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Paper Citation


in Harvard Style

Schiendorfer A., Steghöfer J. and Reif W. (2014). Synthesis and Abstraction of Constraint Models for Hierarchical Resource Allocation Problems . In Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-016-1, pages 15-27. DOI: 10.5220/0004757700150027


in Bibtex Style

@conference{icaart14,
author={Alexander Schiendorfer and Jan-Philipp Steghöfer and Wolfgang Reif},
title={Synthesis and Abstraction of Constraint Models for Hierarchical Resource Allocation Problems},
booktitle={Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2014},
pages={15-27},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004757700150027},
isbn={978-989-758-016-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Synthesis and Abstraction of Constraint Models for Hierarchical Resource Allocation Problems
SN - 978-989-758-016-1
AU - Schiendorfer A.
AU - Steghöfer J.
AU - Reif W.
PY - 2014
SP - 15
EP - 27
DO - 10.5220/0004757700150027