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Shortest paths with a cost constraint: a probabilistic analysis

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 Added by Tomasz Tkocz
 Publication date 2020
  fields
and research's language is English




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We consider a constrained version of the shortest path problem on the complete graphs whose edges have independent random lengths and costs. We establish the asymptotic value of the minimum length as a function of the cost-budget within a wide range.

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In 1903, noted puzzle-maker Henry Dudeney published The Spider and the Fly puzzle, which asks for the shortest path along the surfaces of a square prism between two points (source and target) located on the square faces, and surprisingly showed that the shortest path traverses five faces. Dudeneys source and target points had very symmetrical locations; in this article, we allow the source and target points to be anywhere in the interior of opposite faces, but now require the square prism to be a cube. In this context, we find that, depending on source and target locations, a shortest path can traverse either three or four faces, and we investigate the conditions that lead to four-face solutions and estimate the probability of getting a four-face shortest path. We utilize a combination of numerical calculations, elementary geometry, and transformations we call corner moves of cube unfolding diagrams,
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104 - Haitao Wang 2021
Given a set of pairwise disjoint polygonal obstacles in the plane, finding an obstacle-avoiding Euclidean shortest path between two points is a classical problem in computational geometry and has been studied extensively. Previously, Hershberger and Suri [SIAM J. Comput. 1999] gave an algorithm of $O(nlog n)$ time and $O(nlog n)$ space, where $n$ is the total number of vertices of all obstacles. Recently, by modifying Hershberger and Suris algorithm, Wang [SODA 2021] reduced the space to $O(n)$ while the runtime of the algorithm is still $O(nlog n)$. In this paper, we present a new algorithm of $O(n+hlog h)$ time and $O(n)$ space, provided that a triangulation of the free space is given, where $h$ is the number of obstacles. The algorithm, which improves the previous work when $h=o(n)$, is optimal in both time and space as $Omega(n+hlog h)$ is a lower bound on the runtime. Our algorithm builds a shortest path map for a source point $s$, so that given any query point $t$, the shortest path length from $s$ to $t$ can be computed in $O(log n)$ time and a shortest $s$-$t$ path can be produced in additional time linear in the number of edges of the path.
The determination of collision-free shortest paths among growing discs has previously been studied for discs with fixed growing rates. Here, we study a more general case of this problem, where: (1) the speeds at which the discs are growing are polynomial functions of degree $dd$, and (2) the source and destination points are given as query points. We show how to preprocess the $n$ growing discs so that, for two given query points $s$ and $d$, a shortest path from $s$ to $d$ can be found in $O(n^2 log (dd n))$ time. The preprocessing time of our algorithm is $O(n^2 log n + k log k)$ where $k$ is the number of intersections between the growing discs and the tangent paths (straight line paths which touch the boundaries of two growing discs). We also prove that $k in O(n^3dd)$.
132 - Anil Maheshwari , Arash Nouri , 2018
This paper presents an optimal $Theta(n log n)$ algorithm for determining time-minimal rectilinear paths among $n$ transient rectilinear obstacles. An obstacle is transient if it exists in the scene only for a specific time interval, i.e., it appears and then disappears at specific times. Given a point robot moving with bounded speed among transient rectilinear obstacles and a pair of points $s$, $d$, we determine a time-minimal, obstacle-avoiding path from $s$ to $d$. The main challenge in solving this problem arises as the robot may be required to wait for an obstacle to disappear, before it can continue moving toward the destination. Our algorithm builds on the continuous Dijkstra paradigm, which simulates propagating a wavefront from the source point. We also solve a query version of this problem. For this, we build a planar subdivision with respect to a fixed source point, so that minimum arrival time to any query point can be reported in $O(log n)$ time, using point location for the query point in this subdivision.
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