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

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BIBLE

,A Frequency-Competitive Query Strategy for?Maintaining Low Collision Potential Among Moving Entitieon one another at a fixed time if their separation is less than some specified threshold. Encroachment, of concern in many settings such as collision avoidance, may be unavoidable. However, the associated difficulties are compounded if there is uncertainty about the precise location of entities, giv

gonioscopy

,Approximating Maximum Edge 2-Coloring by?Normalizing Graphs,rs. The problem maximum edge 2-coloring (.) is to find an edge 2-coloring in a graph . with the goal to . the number of colors. For a relevant graph class, . models anti-Ramsey numbers and it was considered in network applications. For the problem a 2-approximation algorithm is known, and if the inp

Endearing

,An Improved Deterministic Algorithm for?the?Online Min-Sum Set Cover Problem,thm has to maintain the time-varying permutation of the list of . elements, and serve a sequence of requests .. Each . is a subset of elements of cardinality at most?.. For a requested set ., an online algorithm has to pay the cost equal to the position of the first element from . on its list. Then,

Obligatory

Greedy Minimum-Energy Scheduling,dividual release times, deadlines, and processing volumes must be scheduled across . parallel processors while minimizing the consumed energy. When idle, each processor can be turned off to save energy, while turning it on requires a fixed amount of energy. For the special case of a single processor

ironic

,Scheduling with?Speed Predictions,the context of scheduling, very recent work has leveraged machine-learned predictions to design algorithms that achieve improved approximation ratios in settings where the processing times of the jobs are initially unknown. In this paper, we study the speed-robust scheduling problem where the speeds

真實的你

,The Power of?Amortization on?Scheduling with?Explorable Uncertainty,entially reduced by testing the job, which also takes time. The objective is to schedule all jobs on a single machine with a minimum total completion time. The challenge lies in deciding which jobs to test and the order of testing/processing jobs..The online problem was first introduced with unit te

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meditation

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