Population Based Methods for Optimising Infinite Behaviours of Timed Automata

Authors Lewis Tolonen, Tim French, Mark Reynolds



PDF
Thumbnail PDF

File

LIPIcs.TIME.2018.22.pdf
  • Filesize: 0.83 MB
  • 22 pages

Document Identifiers

Author Details

Lewis Tolonen
  • The University of Western Australia
Tim French
  • The University of Western Australia
Mark Reynolds
  • The University of Western Australia

Cite AsGet BibTex

Lewis Tolonen, Tim French, and Mark Reynolds. Population Based Methods for Optimising Infinite Behaviours of Timed Automata. In 25th International Symposium on Temporal Representation and Reasoning (TIME 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 120, pp. 22:1-22:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.TIME.2018.22

Abstract

Timed automata are powerful models for the analysis of real time systems. The optimal infinite scheduling problem for double-priced timed automata is concerned with finding infinite runs of a system whose long term cost to reward ratio is minimal. Due to the state-space explosion occurring when discretising a timed automaton, exact computation of the optimal infinite ratio is infeasible. This paper describes the implementation and evaluation of ant colony optimisation for approximating the optimal schedule for a given double-priced timed automaton. The application of ant colony optimisation to the corner-point abstraction of the automaton proved generally less effective than a random method. The best found optimisation method was obtained by formulating the choice of time delays in a cycle of the automaton as a linear program and utilizing ant colony optimisation in order to determine a sequence of profitable discrete transitions comprising an infinite behaviour.

Subject Classification

ACM Subject Classification
  • Theory of computation → Automata over infinite objects
Keywords
  • Timed Automata
  • Heuristic Search
  • Ant Colony Optimisation

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. R Alur and D.L. Dill. A theory of timed automata. Theoretical Computer Science, 126(2):183-235, 1994. Google Scholar
  2. Gerd Behrmann, Ansgar Fehnker, Thomas Hune, Kim Guldstrand Larsen, Paul Pettersson, Judi Romijn, and Frits W. Vaandrager. Minimum-cost reachability for priced timed automata. In Proceedings of the 4th International Workshop on Hybrid Systems: Computation and Control, HSCC '01, pages 147-161, 2001. Google Scholar
  3. Gerd Behrmann, Kim G. Larsen, and Jacob I. Rasmussen. Priced timed automata: Algorithms and applications. In in International Symposium Formal Methods for Components and Objects (FMCO, pages 162-182, 2005. Google Scholar
  4. Patricia Bouyer, Ed Brinksma, and Kim G. Larsen. Optimal infinite scheduling for multi-priced timed automata. Formal Methods in System Design, 32(1):3-23, 2008. Google Scholar
  5. A. Charnes and W. W. Cooper. Programming with linear fractional functionals. Naval Research Logistics Quarterly, 9(3‐4):181-186, 1962. URL: http://dx.doi.org/10.1002/nav.3800090303.
  6. George B Dantzig. Maximization of a linear function of variables subject to linear inequalities. Activity analysi of production and allocation, 1951. Google Scholar
  7. Ali Dasdan, Sandy S. Irani, and Rajesh K. Gupta. Efficient algorithms for optimum cycle mean and optimum cost to time ratio problems. In Proceedings of the 36th Annual ACM/IEEE Design Automation Conference, DAC '99, pages 37-42, 1999. Google Scholar
  8. Alexandre David, Daniel Ejsing-Duun, Lisa Fontani, Kim G. Larsen, Vasile Popescu, and Jacob Haubach Smedegård. Optimal infinite runs in one-clock priced timed automata. Annual Doctoral Workshop on Mathematical and Engineering Methods in Computer Science (MEMICS), 2011. Google Scholar
  9. M. Dorigo, V. Maniezzo, and A. Colorni. Ant system: Optimization by a colony of cooperating agents. Trans. Sys. Man Cyber. Part B, 26(1):29-41, 1996. Google Scholar
  10. Marco Dorigo and Luca Maria Gambardella. Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation, 1(1):53-66, 1997. Google Scholar
  11. Peter Niebert, Stavros Tripakis, and Sergio Yovine. Minimum-time reachability for timed automata. In IEEE Mediteranean Control Conference, 2000. Google Scholar
  12. Krzysztof Socha and Marco Dorigo. Ant colony optimization for continuous domains. European Journal of Operational Research, 185(3):1155-1173, 2008. URL: http://dx.doi.org/10.1016/j.ejor.2006.06.046.
  13. P Soustek, R Matousek, J Dvorak, and J Bednar. Canadian traveller problem: A solution using antcolony optimization. In Proceedings of 19th International Conference on Soft Computing – MENDEL 2013, page 439–444, 2013. Google Scholar
  14. Daniel A. Spielman and Shang-Hua Teng. Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time. J. ACM, 51(3):385-463, 2004. URL: http://dx.doi.org/10.1145/990308.990310.
  15. Thomas Stützle and Holger H. Hoos. Max–min ant system. Future Generation Computer Systems, 16(8):889-914, 2000. URL: http://dx.doi.org/10.1016/S0167-739X(00)00043-1.
  16. Stavros Tripakis and Sergio Yovine. Analysis of timed systems using time-abstracting bisimulations. Form. Methods Syst. Des., 18(1):25-68, 2001. Google Scholar
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail