Abstract
In classic optimization theory, the concept of stability refers to the study of how much and in which way the optimal solutions of a given minimization problem Π can vary as a function of small perturbations of the input data. Motivated by congestion problems arising in shortest-path based communication networks, in this paper we restrict ourselves to the case in which Π is actually a network design problem on a given graph G = (V,E,w) of |V| = n nodes, |E| = m edges, and with a positive real weight w(e) on each edge e ∈ E. We focus on a subclass of perturbations, that we call stretching perturbations, in which the weights of the edges of G can be increased by at most a fixed multiplicative real factor λ ≥ 1.
For this class of perturbations, we address the problem of computing the stability number of any given subgraph H of G containing at least an optimal solution of Π, namely the maximum stretching factor for which H keeps on maintaining an optimal solution. Furthermore, given a stretching factor λ, we study the problem of constructing a minimal subgraph of G with stability number greater or equal to λ.
We develop a general technique to solve both problems. By applying this technique to the minimum spanning tree and the single-source shortest paths tree (SPT) problems, we obtain \({\cal O}(m\alpha(m,n))\) and \({\cal O}(mn(m+n \log n))\) time algorithms, respectively, where α(·,·) is the functional inverse of Ackermann’s function. Furthermore, for the SPT problem, we show that if H coincides with the set of all optimal solutions, then the time complexity can be reduced to \({\cal O}(mn)\). Finally, for the single-source single-destination shortest path problem, if the optimal solutions of the input instance happen to form a set of vertex-disjoint paths, and H coincides with this set, then we show that we can compute the stability number in \({\cal O}(mn + n^2 \log n)\) time.
Part of this work has been developed while the fourth author was visiting ETH Zurich.
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References
Beyer, H.-G., Sendhoff, B.: Robust optimization - a comprehensive survey. Computer Methods in Applied Mechanics and Engineering 196(33-34), 3190–3218 (2007)
Dixon, B., Rauch, M., Tarjan, R.E.: Verification and sensitivity analysis of minimum spanning trees in linear time. SIAM J. Comput. 21(6), 1184–1192 (1992)
Gal, T., Greenberg, H.J. (eds.): Advances in sensitivity analysis and parametric programming. Int. Series in Operations Research and Management Science, vol. 6. Kluwer Academic Publishers, Boston (1997)
Kouvelis, P., Yu, G.: Robust discrete optimization and its applications. Kluwer Academic Publishers, Dordrecht (1997)
Pettie, S., Ramachandran, V.: An optimal minimum spanning tree algorithm. J. ACM 49(1), 16–34 (2002)
Pettie, S.: Sensitivity analysis of minimum spanning trees in sub-inverse-Ackermann time. In: Deng, X., Du, D.-Z. (eds.) ISAAC 2005. LNCS, vol. 3827, pp. 964–973. Springer, Heidelberg (2005)
Shier, D.R., Witzgall, C.: Edge tolerances in shortest path and network flow problems. Networks 10(4), 277–291 (1980)
Tarjan, R.E.: Sensitivity analysis of minimum spanning trees and shortest path trees. Inf. Proc. Letters 14(1), 30–33 (1982)
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Bilò, D., Gatto, M., Gualà, L., Proietti, G., Widmayer, P. (2010). Stability of Networks in Stretchable Graphs. In: Kutten, S., Žerovnik, J. (eds) Structural Information and Communication Complexity. SIROCCO 2009. Lecture Notes in Computer Science, vol 5869. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11476-2_9
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DOI: https://doi.org/10.1007/978-3-642-11476-2_9
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