2007 Proceedings of the Ninth Workshop on Algorithm Engineering and Experiments (ALENEX) 2007
DOI: 10.1137/1.9781611972870.12
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Locating Guards for Visibility Coverage of Polygons

Abstract: We propose heuristics for visibility coverage of a polygon with the fewest point guards. This optimal coverage problem, often called the "art gallery problem", is known to be NP-hard, so most recent research has focused on heuristics and approximation methods. We evaluate our heuristics through experimentation, comparing the upper bounds on the optimal guard number given by our methods with computed lower bounds based on heuristics for placing a large number of visibility-independent "witness points". We give … Show more

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Cited by 20 publications
(14 citation statements)
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“…Previous work mostly consists of heuristics [Amit et al 2007] with good practical performance. To the best of our knowledge, there is little work on good lower bounds.…”
Section: Related Workmentioning
confidence: 99%
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“…Previous work mostly consists of heuristics [Amit et al 2007] with good practical performance. To the best of our knowledge, there is little work on good lower bounds.…”
Section: Related Workmentioning
confidence: 99%
“…To the best of our knowledge, there is little work on good lower bounds. Amit et al [2007] are the only ones to consider a lower bound for the general AGP, with the entire polygon to cover. They use the lower bound to compare heuristic solutions, with the guards taken from different candidate sets, such as vertices and more enhanced points.…”
Section: Related Workmentioning
confidence: 99%
“…Since the corresponding minimization problem has been proven NPhard [9] even for orthogonal polygons [10], placement of suboptimal numbers of guards has been studied [2], as well as a few approximation algorithms [1].…”
Section: Introductionmentioning
confidence: 99%
“…There are several works where approximation algorithms were developed to solve the MSG problem [3,9] and to compute multiple watchmen routes, a variant of the MSG problem [15]. In a recent work, metaheuristics techniques have proven to behave very well when solving the MSG problem [1].…”
Section: Introduction Related Work and Problem Definitionmentioning
confidence: 99%