The sequential sum problem and performance bounds on the greedy algorithm for the on-line Steiner problem

This article is motivated by versions of the dynamic or “on‐line” Steiner tree problem (OST) introduced by Imase and Waxman [4]. In this problem one is given an edge‐weighted graph G and a sequence σ = (x1,…,xn) of distinct vertices of G. The requirement is to construct for each i ≤ n a tree Ti span...

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Published inNetworks Vol. 45; no. 3; pp. 143 - 164
Main Authors Miller, Zevi, Pritikin, Dan, Perkel, Manley, Sudborough, I.H.
Format Journal Article
LanguageEnglish
Published Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.05.2005
John Wiley & Sons
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ISSN0028-3045
1097-0037
DOI10.1002/net.20057

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Summary:This article is motivated by versions of the dynamic or “on‐line” Steiner tree problem (OST) introduced by Imase and Waxman [4]. In this problem one is given an edge‐weighted graph G and a sequence σ = (x1,…,xn) of distinct vertices of G. The requirement is to construct for each i ≤ n a tree Ti spanning the first i vertices of σ subject to the condition that Ti−1⫅Ti for all i, where Ti is constructed without knowledge of the remaining vertices xj, j > i. The goal of the on‐line Steiner problem is to minimize the performance ratio; that is, the maximum (over 1 ≤ i ≤ n) of the ratio of the weight of Ti to the weight of the minimum weight tree in G spanning the first i vertices (the latter tree is called the “Steiner tree” for these vertices). In [4] a lower bound of 1 + ½⌊ log2(n−1)⌋ was proved for this ratio. The authors further made the interesting conjecture that there is some on‐line algorithm for the OST whose performance ratio achieves this lower bound. We show that a strong form of the greedy algorithm achieves a ratio that converges to the conjectured ½log2(k) + O(1) as the proportion of degree 2 vertices in the instance graph grows. Our results also imply improvements in certain cases on the known upper bound ⌈log2(n)⌉ for the performance ratio of the greedy algorithm. Our approach is to study a related graph parameter. For each sequence σ as above, define the associated cost $$L(\sigma) = \sum_{i = 2}^n c(i,\sigma),$$ where c(i,σ) = min1 ≤ t < idist(xi, xt). Then let Opt(n, G) be the maximum of L(σ) over all such sequences σ of length n. The problem of, given n and G, determining Opt(n, G) we call the Sequential Sum Problem (SSP). In this article we analyze the SSP, obtaining exact values and bounds on Opt(n, G) and relating these bounds to the greedy algorithm for the OST. For example, we calculate Opt(n, P) for the path P, and obtain a surprising characterization of all length n sequences σ which realize Opt(n, P). By analyzing Opt(n, P) for the “continuous” path, we derive upper bounds on the performance ratio of the greedy algorithm for the OST in arbitrary graphs. On the other hand, generalizing the lower bound argument of [4] we show that there are instances of OST, which can significantly “fool” any on‐line algorithm for OST. Specifically, given any tree T normalized to have total edge weight 1, we construct a graph G and a length k ≤ |V(T)| sequence σ of vertices of G for which the performance ratio of any on‐line algorithm for the OST with input σ is lower bounded by Opt(k, T). Finally, we show that the SSP for arbitrary G is NP‐complete. © 2005 Wiley Periodicals, Inc. NETWORKS, Vol. 45(3), 143–164 2005
Bibliography:istex:AD62BBC32272B54E481001A5BEF815F2919D6F80
ark:/67375/WNG-B3D0LWZL-F
ArticleID:NET20057
ISSN:0028-3045
1097-0037
DOI:10.1002/net.20057