Titlebook: Algorithms and Data Structures; 5th International Wo Frank Dehne,Andrew Rau-Chaplin,Roberto Tamassia Conference proceedings 1997 Springer-V

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Dynamic motion planning in low obstacle density environments,gh worst-case running times. The weak and realistic low obstacle density (L.O.D.) assumption results in linear complexity in the number of obstacles of the free space [1l]. In this paper we consider the dynamic version of the motion planning problem in which a robot moves among moving polygonal obst

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Finding cores of limited length, nodes in the tree. This problem has been examined under different constraints on the tree and on the set of paths, from which the core can be chosen. For all cases, we present linear or almost linear time algorithms, which improves the previous results due to Lo and Peng, J. Algorithms Vol. 20, 199

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Approximation algorithms for a genetic diagnostics problem,osis of a important class of chromosomal aberrations. An optimal solution to WDC would enable us to define a genetic assay that maximizes the diagnostic power for a specified cost of laboratory work. We develop approximation algorithms for WDC by making use of the well-known problem SET COVER for wh

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Cartographic line simplication and polygon CSG formulae in ,(, log,,) time,e, such as a coastline, on a map. A constructive solid geometry (CSG) conversion for a polygon takes a list of vertices and produces a formula representing the polygon as an intersection and union of primitive halfspaces. By using a data structure that supports splitting convex hulls and finding ext

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A linear-time algorithm for the 1-mismatch problem, run of consecutive columns, that have some particular property. The . is to locate all maximal regions in a given alignment for which there exists a (not necessarily unique) “center” sequence such that inside the region alignment rows are within Hamming distance 1 from the center. We first describe