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Titlebook: Approximation and Online Algorithms; 21st International W Jarosław Byrka,Andreas Wiese Conference proceedings 2023 The Editor(s) (if applic

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,Probleme der adhäsiven Perikarditis,-hard to obtain an approximation ratio better than 1.5. We show that if the input graph has a perfect matching, there is a polynomial time 1.625-approximation and if the graph is claw-free or if the maximum degree of the input graph is at most three (i.e., the graph is subcubic), there is a polynomial time 1.5-approximation algorithm for ..
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,Approximating Maximum Edge 2-Coloring by Normalizing Graphs,-hard to obtain an approximation ratio better than 1.5. We show that if the input graph has a perfect matching, there is a polynomial time 1.625-approximation and if the graph is claw-free or if the maximum degree of the input graph is at most three (i.e., the graph is subcubic), there is a polynomial time 1.5-approximation algorithm for ..
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0302-9743 hanism design, network design, packing and covering, paradigms for the design and analysis of approximation and online algorithms, resource augmentation, and scheduling problems.978-3-031-49814-5978-3-031-49815-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
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F. Kraus,Erich Meyer,L. Langsteinocessing volume. Our algorithm has a running time of ., where . is the difference between the last deadline and the earliest release time, and . is the running time of a maximum flow calculation in a network of . nodes.
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Calcium Metabolism and Kidney Disease,in general, make the problem NP-hard. We paint an almost complete picture of the evolving complexity landscape, drawing the line between easy and hard. One of our main algorithmic contributions relies on a deep structural result on the maximum imbalance of an optimal schedule, based on a subtle connection to Hilbert bases of a related convex cone.
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,An Improved Deterministic Algorithm for the Online Min-Sum Set Cover Problem,previous constructive bound of . by Fotakis et al. [ICALP ’20]. Furthermore, we show that our algorithm attains an asymptotically optimal competitive ratio of .(.) when compared to the best fixed permutation of elements.
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Greedy Minimum-Energy Scheduling,ocessing volume. Our algorithm has a running time of ., where . is the difference between the last deadline and the earliest release time, and . is the running time of a maximum flow calculation in a network of . nodes.
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