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  • Titel: Approximation Strategies for Generalized Binary Search in Weighted Trees
  • Beteiligte: Dereniowski, Dariusz [Verfasser:in]; Kosowski, Adrian [Verfasser:in]; Uznanski, Przemyslaw [Verfasser:in]; Zou, Mengchuan [Verfasser:in]
  • Erschienen: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2017
  • Sprache: Englisch
  • DOI: https://doi.org/10.4230/LIPIcs.ICALP.2017.84
  • Schlagwörter: Trees ; Vertex Ranking ; Graph Search ; Approximation Algorithm ; Binary Search ; Adaptive Algorithm
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  • Beschreibung: We consider the following generalization of the binary search problem. A search strategy is required to locate an unknown target node t in a given tree T. Upon querying a node v of the tree, the strategy receives as a reply an indication of the connected component of T\{v} containing the target t. The cost of querying each node is given by a known non-negative weight function, and the considered objective is to minimize the total query cost for a worst-case choice of the target. Designing an optimal strategy for a weighted tree search instance is known to be strongly NP-hard, in contrast to the unweighted variant of the problem which can be solved optimally in linear time. Here, we show that weighted tree search admits a quasi-polynomial time approximation scheme (QPTAS): for any 0 < epsilon < 1, there exists a (1+epsilon)-approximation strategy with a computation time of n^O(log n / epsilon^2). Thus, the problem is not APX-hard, unless NP is contained in DTIME(n^O(log n)). By applying a generic reduction, we obtain as a corollary that the studied problem admits a polynomial-time O(sqrt(log n))-approximation. This improves previous tilde-O(log n)-approximation approaches, where the tilde-O-notation disregards O(poly log log n)-factors.
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