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Titlebook: Algorithms and Computation; 19th International S Seok-Hee Hong,Hiroshi Nagamochi,Takuro Fukunaga Conference proceedings 2008 Springer-Verla

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https://doi.org/10.1007/978-3-662-63618-3hms which require no extra array of size depending on input size . but use only constant working storage cells (variables), each having .(log.) bits. As an example, consider a problem of finding the median among . given numbers. A linear-time algorithm for the problem is well known. An ordinary impl
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https://doi.org/10.1007/978-3-662-31651-1 there exists a path (named a Manhattan path) of the length exactly the Manhattan distance between . and .. The Minimum Manhattan Network problem is to find a Manhattan network of the minimum length, ., the total length of the segments of the network is to be minimized. In this paper we present a 2-
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Alternativen der medialen Entwicklungants of recoloring a colored graph with minimal cost such that the resulting coloring is convex. Two variants of the problem are shown to be .-hard on trees even if in the initial coloring each color is used to color only a bounded number of vertices. For graphs of bounded treewidth, we present a po
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Alternativen der medialen Entwicklungltiobjective problem where . types of points (customers) in the plane have to be covered by disks (base stations) such that the number of disks is minimized and for each type of points, the number of covered points is maximized. Our approximation scheme can be extended so that it works with the foll
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Michael Markert,Ina Katharina Uphoff and performances of online algorithms have been analyzed by the competitive analysis. The previous best upper and lower bounds on the competitive ratio were 10 and 5/3, respectively. In this paper, we improve them to 7 and 2, respectively. We also show that our analysis for the upper bound is tight
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Michael Markert,Ina Katharina Uphoffe colored using as few colors as possible. In the max-coloring problem, a fixed number of colors is given, and as many edges as possible should be colored. Previous analysis using the competitive ratio has not separated the performance of First-Fit and Next-Fit, but intuition suggests that First-Fit
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