SearcharxivSearch

arXiv subjects

Elmar Langetepe

Publications and source records attributed to Elmar Langetepe.

17 recordsLinked to original sources

Online Competitive Searching for Rays in the Half-plane

We consider the problem of searching for rays (or lines) in the half-plane. The given problem turns out to be a very natural extension of the cow-path problem that is lifted into the half-plane and the problem can also directly be motivated by a 1.5-dimensional terrain search problem. We present and analyse an efficient strategy for our setting and guarantee a competitive ratio of less than 9.12725 in the worst case and also prove a lower bound of at least 9.06357 for any strategy. Thus the given strategy is almost optimal, the gap is less than 0.06368. By appropriate adjustments for the terrain search problem we can improve on former results and present geometrically motivated proof arguments. As expected, the terrain itself can only be helpful for the searcher that competes against the unknown shortest path. We somehow extract the core of the problem.

cs.CG

NP-hardness and a PTAS for the Euclidean Steiner Line Problem

The Euclidean Steiner Tree Problem (EST) seeks a minimum-cost tree interconnecting a given set of terminal points in the Euclidean plane, allowing the use of additional intersection points. In this paper, we consider two variants that include an additional straight line $γ$ with zero cost, which must be incorporated into the tree. In the Euclidean Steiner fixed Line Problem (ESfL), this line is given as input and can be treated as a terminal. In contrast, the Euclidean Steiner Line Problem (ESL) requires determining the optimal location of $γ$. Despite recent advances, including heuristics and a 1.214-approximation algorithm for both problems, a formal proof of NP-hardness has remained open. In this work, we close this gap by proving that both the ESL and ESfL are NP-hard. Additionally, we prove that both problems admit a polynomial-time approximation scheme (PTAS), by demonstrating that approximation algorithms for the EST can be adapted to the ESL and ESfL with appropriate modifications. Specifically, we show ESfL$\leq_{\text{PTAS}}$EST and ESL$\leq_{\text{PTAS}}$EST, i.e., provide a PTAS reduction to the EST.

cs.CG

Simple Grid Polygon Online Exploration Revisited

Due to some significantly contradicting research results, we reconsider the problem of the online exploration of a simple grid cell environment. In this model an agent attains local information about the direct four-neigbourship of a current grid cell and can also successively build a map of all detected cells. Beginning from a starting cell at the boundary of the environment, the agent has to visit any cell of the grid environment and finally has to return to its starting position. The performance of an online strategy is given by competitive analysis. We compare the number of overall cell visits (number of steps) of an online strategy to the number of such visits in the optimal offline solution under full information of the environment in advance. The corresponding worst-case ratio gives the competitive ratio. The aforementioned contradiction among two publications turns out to be as follows: There is a journal publication that claims to present an optimal competitive strategy with ratio 7/6 and a former conference paper that presents a lower bound of 20/17. In this note we extract the flaw in the upper bound and also present a new slightly improved and (as we think) simplified general lower bound of 13/11.

cs.CG

Analysis of a Greedy Heuristic for the Labeling of a Map with a Time-Window Interface

In this paper, we analyze the approximation quality of a greedy heuristic for automatic map labeling. As input, we have a set of events, each associated with a label at a fixed position, a timestamp, and a weight. Let a time-window labeling be a selection of these labels such that all corresponding timestamps lie in a queried time window and no two labels overlap. A solution to the time-window labeling problem consists of a data structure that encodes a time-window labeling for each possible time window; when a user specifies a time window of interest using a slider interface, we query the data structure for the corresponding labeling. We define the quality of a time-window labeling solution as the sum of the weights of the labels in each time-window labeling, integrated over all time windows. We aim at maximizing the quality under the condition that a label may never disappear when the user shrinks the time window. In this paper, we analyze how well a greedy heuristic approximates the maximum quality that can be realized under this condition. On the one hand, we present an instance with square labels of equal size and equal weight for which the greedy heuristic fails to find a solution of at least 1/4 of the quality of an optimal solution. On the other hand, we prove that the greedy heuristic does guarantee a solution with at least 1/8 of the quality of an optimal solution. In the case of disk-shaped labels of equal size and equal weight, the greedy heuristic gives a solution with at least 1/10 of the quality of an optimal solution. If the labels are squares or disks of equal size and the maximum weight divided by the minimum weight is at most b, then the greedy heuristic has approximation ratio Theta(log b).

cs.CG

Minimum-Error Triangulations for Sea Surface Reconstruction

We apply state-of-the-art computational geometry methods to the problem of reconstructing a time-varying sea surface from tide gauge records. Our work builds on a recent article by Nitzke et al.~(Computers \& Geosciences, 157:104920, 2021) who have suggested to learn a triangulation $D$ of a given set of tide gauge stations. The objective is to minimize the misfit of the piecewise linear surface induced by $D$ to a reference surface that has been acquired with satellite altimetry. The authors restricted their search to k-order Delaunay ($k$-OD) triangulations and used an integer linear program in order to solve the resulting optimization problem. In geometric terms, the input to our problem consists of two sets of points in $\mathbb{R}^2$ with elevations: a set $\mathcal{S}$ that is to be triangulated, and a set $\mathcal{R}$ of reference points. Intuitively, we define the error of a triangulation as the average vertical distance of a point in $\mathcal{R}$ to the triangulated surface that is obtained by interpolating elevations of $\mathcal{S}$ linearly in each triangle. Our goal is to find the triangulation of $\mathcal{S}$ that has minimum error with respect to $\mathcal{R}$. In our work, we prove that the minimum-error triangulation problem is NP-hard and cannot be approximated within any multiplicative factor in polynomial time unless $P=NP$. At the same time we show that the problem instances that occur in our application (considering sea level data from several hundreds of tide gauge stations worldwide) can be solved relatively fast using dynamic programming when restricted to $k$-OD triangulations for $k\le 7$. In particular, instances for which the number of connected components of the so-called $k$-OD fixed-edge graph is small can be solved within few seconds.

cs.CG

A New Model in Firefighting Theory

Continuous and discrete models for firefighting problems are well-studied in Theoretical Computer Science. We introduce a new, discrete, and more general framework based on a hexagonal cell graph to study firefighting problems in varied terrains. We present three different firefighting problems in the context of this model; for two of which, we provide efficient polynomial time algorithms and for the third, we show NP-completeness. We also discuss possible extensions of the model and their implications on the computational complexity.

cs.CG

Shortest-Path-Preserving Rounding

Various applications of graphs, in particular applications related to finding shortest paths, naturally get inputs with real weights on the edges. However, for algorithmic or visualization reasons, inputs with integer weights would often be preferable or even required. This raises the following question: given an undirected graph with non-negative real weights on the edges and an error threshold $\varepsilon$, how efficiently can we decide whether we can round all weights such that shortest paths are maintained, and the change of weight of each shortest path is less than $\varepsilon$? So far, only for path-shaped graphs a polynomial-time algorithm was known. In this paper we prove, by reduction from 3-SAT, that, in general, the problem is NP-hard. However, if the graph is a tree with $n$ vertices, the problem can be solved in $O(n^2)$ time.

cs.CC

Geometric Firefighting in the Half-plane

In 2006, Alberto Bressan suggested the following problem. Suppose a circular fire spreads in the Euclidean plane at unit speed. The task is to build, in real time, barrier curves to contain the fire. At each time $t$ the total length of all barriers built so far must not exceed $t \cdot v$, where $v$ is a speed constant. How large a speed $v$ is needed? He proved that speed $v>2$ is sufficient, and that $v>1$ is necessary. This gap of $(1,2]$ is still open. The crucial question seems to be the following. {\em When trying to contain a fire, should one build, at maximum speed, the enclosing barrier, or does it make sense to spend some time on placing extra delaying barriers in the fire's way?} We study the situation where the fire must be contained in the upper $L_1$ half-plane by an infinite horizontal barrier to which vertical line segments may be attached as delaying barriers. Surprisingly, such delaying barriers are helpful when properly placed. We prove that speed $v=1.8772$ is sufficient, while $v >1.66$ is necessary.

cs.CG

Evolutionary learning of fire fighting strategies

The dynamic problem of enclosing an expanding fire can be modelled by a discrete variant in a grid graph. While the fire expands to all neighbouring cells in any time step, the fire fighter is allowed to block $c$ cells in the average outside the fire in the same time interval. It was shown that the success of the fire fighter is guaranteed for $c>1.5$ but no strategy can enclose the fire for $c\leq 1.5$. For achieving such a critical threshold the correctness (sometimes even optimality) of strategies and lower bounds have been shown by integer programming or by direct but often very sophisticated arguments. We investigate the problem whether it is possible to find or to approach such a threshold and/or optimal strategies by means of evolutionary algorithms, i.e., we just try to learn successful strategies for different constants $c$ and have a look at the outcome. The main general idea is that this approach might give some insight in the power of evolutionary strategies for similar geometrically motivated threshold questions. We investigate the variant of protecting a highway with still unknown threshold and found interesting strategic paradigms. Keywords: Dynamic environments, fire fighting, evolutionary strategies, threshold approximation

cs.NE

Exact VC-dimension for $L_1$-visibility of points in simple polygons

The VC-dimension plays an important role for the algorithmic problem of guarding art galleries efficiently. We prove that inside a simple polygon at most $5$ points can be shattered by $L_1$-visibility polygons and give an example where 5 points are shattered. The VC-dimension is exactly $5$. The proof idea for the upper bound is different from previous approaches. Keywords: Art gallery, VC-dimension, $L_1$-visibility, polygons

cs.CG

Optimal online escape path against a certificate

More than fifty years ago, Bellman asked for the best escape path within a known forest but for an unknown starting position. This deterministic finite path is the shortest path that leads out of a given environment from any starting point. There are some worst case positions where the full path length is required. Up to now such a fixed ultimate optimal escape path for a known shape for any starting position is only known for some special convex shapes (i.e., circles, strips of a given width, fat convex bodies, some isosceles triangles). Therefore, we introduce a different, simple and intuitive escape path, the so-called certificate path. This escape path depends on the starting position s and takes the distances from s to the outer boundary of the environment into account. Due to the additional information, the certificate path always (for any position s) leaves the environment earlier than the ultimate escape path, in the above convex examples. Next we assume that fewer information is available. Neither the precise shape of the envir- onment, nor the location of the starting point is known. For a class of environments (convex shapes and shapes with kernel positions), we design an online strategy that always leaves the environment. We show that the path length for leaving the environment is always shorter than 3.318764 the length of the corresponding certificate path. We also give a lower bound of 3.313126, which shows that for the above class of environments the factor 3.318764 is (almost) tight.

cs.CG

A Fire Fighter's Problem

Suppose that a circular fire spreads in the plane at unit speed. A single fire fighter can build a barrier at speed $v>1$. How large must $v$ be to ensure that the fire can be contained, and how should the fire fighter proceed? We contribute two results. First, we analyze the natural curve $\mbox{FF}_v$ that develops when the fighter keeps building, at speed $v$, a barrier along the boundary of the expanding fire. We prove that the behavior of this spiralling curve is governed by a complex function $(e^{w Z} - s \, Z)^{-1}$, where $w$ and $s$ are real functions of $v$. For $v>v_c=2.6144 \ldots$ all zeroes are complex conjugate pairs. If $ϕ$ denotes the complex argument of the conjugate pair nearest to the origin then, by residue calculus, the fire fighter needs $Θ( 1/ϕ)$ rounds before the fire is contained. As $v$ decreases towards $v_c$ these two zeroes merge into a real one, so that argument $ϕ$ goes to~0. Thus, curve $\mbox{FF}_v$ does not contain the fire if the fighter moves at speed $v=v_c$. (That speed $v>v_c$ is sufficient for containing the fire has been proposed before by Bressan et al. [7], who constructed a sequence of logarithmic spiral segments that stay strictly away from the fire.) Second, we show that any curve that visits the four coordinate half-axes in cyclic order, and in inreasing distances from the origin, needs speed $v>1.618\ldots$, the golden ratio, in order to contain the fire. Keywords: Motion Planning, Dynamic Environments, Spiralling strategies, Lower and upper bounds

cs.CG

A local strategy for cleaning expanding cellular domains by simple robots

We present a strategy SEP for finite state machines tasked with cleaning a cellular environment in which a contamination spreads. Initially, the contaminated area is of height $h$ and width $w$. It may be bounded by four monotonic chains, and contain rectangular holes. The robot does not know the initial contamination, sensing only the eight cells in its neighborhood. It moves from cell to cell, $d$ times faster than the contamination spreads, and is able to clean its current cell. A speed of $d<\sqrt{2}(h+w)$ is in general not sufficient to contain the contamination. Our strategy SEP succeeds if $d \geq 3(h+w)$ holds. It ensures that the contaminated cells stay connected. Greedy strategies violating this principle need speed at least $d \geq 4(h+w)$; all bounds are up to small additive constants.

cs.DS

Strategic deployment in graphs

Conquerors of old (like, e.g., Alexander the Great or Ceasar) had to solve the following deployment problem. Sufficiently strong units had to be stationed at locations of strategic importance, and the moving forces had to be strong enough to advance to the next location. To the best of our knowledge we are the first to consider the (off-line) graph version of this problem. While being NP-hard for general graphs, for trees the minimum number of agents and an optimal deployment can be computed in optimal polynomial time. Moreover, the optimal solution for the minimum spanning tree of an arbitrary graph G results in a 2-approximation of the optimal solution for G.

cs.DS

Exploring Grid Polygons Online

We investigate the exploration problem of a short-sighted mobile robot moving in an unknown cellular room. To explore a cell, the robot must enter it. Once inside, the robot knows which of the 4 adjacent cells exist and which are boundary edges. The robot starts from a specified cell adjacent to the room's outer wall; it visits each cell, and returns to the start. Our interest is in a short exploration tour; that is, in keeping the number of multiple cell visits small. For abitrary environments containing no obstacles we provide a strategy producing tours of length S <= C + 1/2 E - 3, and for environments containing obstacles we provide a strategy, that is bound by S <= C + 1/2 E + 3H + WCW - 2, where C denotes the number of cells-the area-, E denotes the number of boundary edges-the perimeter-, and H is the number of obstacles, and WCW is a measure for the sinuosity of the given environment.

cs.CG

Exploring Simple Triangular and Hexagonal Grid Polygons Online

We investigate the online exploration problem (aka covering) of a short-sighted mobile robot moving in an unknown cellular environment with hexagons and triangles as types of cells. To explore a cell, the robot must enter it. Once inside, the robot knows which of the 3 or 6 adjacent cells exist and which are boundary edges. The robot's task is to visit every cell in the given environment and to return to the start. Our interest is in a short exploration tour; that is, in keeping the number of multiple cell visits small. For arbitrary environments containing no obstacles we provide a strategy producing tours of length S <= C + 1/4 E - 2.5 for hexagonal grids, and S <= C + E - 4 for triangular grids. C denotes the number of cells-the area-, E denotes the number of boundary edges-the perimeter-of the given environment. Further, we show that our strategy is 4/3-competitive in both types of grids, and we provide lower bounds of 14/13 for hexagonal grids and 7/6 for triangular grids.

cs.CG

Optimal competitive online ray search with an error-prone robot

We consider the problem of finding a door along a wall with a blind robot that neither knows the distance to the door nor the direction towards of the door. This problem can be solved with the well-known doubling strategy yielding an optimal competitive factor of 9 with the assumption that the robot does not make any errors during its movements. We study the case that the robot's movement is erroneous. In this case the doubling strategy is no longer optimal. We present optimal competitive strategies that take the error assumption into account. The analysis technique can be applied to different error models.

cs.CG