Hostname: page-component-cd9895bd7-7cvxr Total loading time: 0 Render date: 2024-12-21T09:57:26.221Z Has data issue: false hasContentIssue false

Critical Path Statistics of Max-Plus Linear Systems with Gaussian Noise

Published online by Cambridge University Press:  30 January 2018

James Hook*
Affiliation:
University of Manchester
*
Postal address: Alan Turing Building, University of Manchester, Oxford Road, Manchester M13 9PL, UK. Email address: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The critical paths of a max-plus linear system with noise are random variables. In this paper we introduce the edge criticalities which measure how often the critical paths traverse each edge in the precedence graph. We also present the parallel path approximation, a novel method for approximating these new statistics as well as the previously studied max-plus exponent. We show that, for low amplitude noise, the critical paths spend most of their time traversing the deterministic maximally weighted cycle and that, as the noise amplitude is increased, the critical paths become more random and their distribution over the edges in the precedence graph approaches a highly uniform measure of maximal entropy.

Type
Research Article
Copyright
© Applied Probability Trust 

References

Baccelli, F. and Hong, D. (2000). Analytic expansions of max-plus Lyapunov exponents. Ann. Appl. Prob. 10, 779827.CrossRefGoogle Scholar
Baccelli, F. L., Cohen, G., Olsder, G. J. and Quadrat, J.-P. (1992). Synchronization and Linearity. John Wiley, Chichester.Google Scholar
Cuninghame-Green, R. A. (1962). Describing industrial processes with interference and approximating their steady-state behaviour. Operat. Res. Quart. 13, 95100.CrossRefGoogle Scholar
Dembo, A. and Zeitouni, O. (1998). Large Deviations Techniques and Applications (Appl. Math. 38), 2nd edn. Springer, New York.Google Scholar
Goverde, R. M. P., Heidergott, B. and Merlet, G. (2011). A coupling approach to estimating the Lyapunov exponent of stochastic max-plus linear systems. Europ. J. Operat. Res. 210, 249257.Google Scholar
Heidergott, B. F. (2007). Max-Plus Linear Stochastic Systems and Perturbation Analysis. Springer, New York.Google Scholar
Mairesse, J. (1997). Products of irreducible random matrices in the (max, +) algebra. Adv. Appl. Prob. 29, 444477.CrossRefGoogle Scholar
Merlet, G. (2008). Cycle time of stochastic max-plus linear systems. Electron. J. Prob. 13, 322340.CrossRefGoogle Scholar
Mittal, Y. and Ylvisaker, D. (1976). Strong laws for the maxima of stationary Gaussian processes. Ann. Prob. 4, 357371.CrossRefGoogle Scholar
Oliveira, P. E. (2012). Asymptotics for Associated Random Variables. Springer, Heidelberg.Google Scholar