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Computing Shortest Paths in the Plane with Removable Obstacles

机译:计算平面中的最短路径,可拆卸障碍物

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We consider the problem of computing a Euclidean shortest path in the presence of removable obstacles in the plane. In particular, we have a collection of pairwise-disjoint polygonal obstacles, each of which may be removed at some cost c_i 0. Given a cost budget C 0, and a pair of points s, t, which obstacles should be removed to minimize the path length from s to t in the remaining workspace? We show that this problem is NP-hard even if the obstacles are vertical line segments. Our main result is a fully-polynomial time approximation scheme (FPTAS) for the case of convex polygons. Specifically, we compute an (1 + epsilon)-approximate shortest path in time O({nh}/{epsilon^2} log n log n/epsilon) with removal cost at most (1+epsilon)C, where h is the number of obstacles, n is the total number of obstacle vertices, and epsilon in (0, 1) is a user-specified parameter. Our approximation scheme also solves a shortest path problem for a stochastic model of obstacles, where each obstacle's presence is an independent event with a known probability. Finally, we also present a data structure that can answer s-t path queries in polylogarithmic time, for any pair of points s, t in the plane.
机译:我们考虑在飞机中可拆卸障碍物存在下计算欧几里德最短路径的问题。特别地,我们具有成对不相交的多边形障碍物的集合,每个障碍物可以在一些成本C_I> 0上被移除。给定成本预算c> 0,以及一对点S,t,应该去除哪个障碍物在剩余工作区中最小化从s到t的路径长度?我们表明,即使障碍是垂直线段,这个问题也是努力的。我们的主要结果是凸多边形的情况是一个全多项式时间近似方案(FPTA)。具体而言,我们计算(1 + epsilon) - 时间o({nh} / {epsilon ^ 2} log n log n / epsilon),最多(1 + epsilon)c,其中h是障碍物数量,n是障碍物顶点的总数,并且(0,1)中的epsilon是用户指定的参数。我们的近似方案还解决了一个最短的路径问题,用于障碍的随机模型,其中每个障碍物的存在是具有已知概率的独立事件。最后,我们还提出了一种数据结构,可以在平面中的任何一对点S中应答波动力学时间中的S-T路径查询。

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