@article{50458,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Consider a set of jobs connected to a directed acyclic task graph with a fixed source and sink. The edges of this graph model precedence constraints and the jobs have to be scheduled with respect to those. We introduce the server cloud scheduling problem, in which the jobs have to be processed either on a single local machine or on one of infinitely many cloud machines. For each job, processing times both on the server and in the cloud are given. Furthermore, for each edge in the task graph, a communication delay is included in the input and has to be taken into account if one of the two jobs is scheduled on the server and the other in the cloud. The server processes jobs sequentially, whereas the cloud can serve as many as needed in parallel, but induces costs. We consider both makespan and cost minimization. The main results are an FPTAS for the makespan objective for graphs with a constant source and sink dividing cut and strong hardness for the case with unit processing times and delays.</jats:p>}},
  author       = {{Maack, Marten and Meyer auf der Heide, Friedhelm and Pukrop, Simon}},
  issn         = {{0178-4617}},
  journal      = {{Algorithmica}},
  keywords     = {{Applied Mathematics, Computer Science Applications, General Computer Science}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Server Cloud Scheduling}}},
  doi          = {{10.1007/s00453-023-01189-x}},
  year         = {{2023}},
}

@article{31479,
  author       = {{Baswana, Surender and Gupta, Shiv and Knollmann, Till}},
  issn         = {{0178-4617}},
  journal      = {{Algorithmica}},
  keywords     = {{Applied Mathematics, Computer Science Applications, General Computer Science}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Mincut Sensitivity Data Structures for the Insertion of an Edge}}},
  doi          = {{10.1007/s00453-022-00978-0}},
  year         = {{2022}},
}

@article{48854,
  abstract     = {{We contribute to the theoretical understanding of randomized search heuristics for dynamic problems. We consider the classical vertex coloring problem on graphs and investigate the dynamic setting where edges are added to the current graph. We then analyze the expected time for randomized search heuristics to recompute high quality solutions. The (1+1) Evolutionary Algorithm and RLS operate in a setting where the number of colors is bounded and we are minimizing the number of conflicts. Iterated local search algorithms use an unbounded color palette and aim to use the smallest colors and, consequently, the smallest number of colors. We identify classes of bipartite graphs where reoptimization is as hard as or even harder than optimization from scratch, i.e., starting with a random initialization. Even adding a single edge can lead to hard symmetry problems. However, graph classes that are hard for one algorithm turn out to be easy for others. In most cases our bounds show that reoptimization is faster than optimizing from scratch. We further show that tailoring mutation operators to parts of the graph where changes have occurred can significantly reduce the expected reoptimization time. In most settings the expected reoptimization time for such tailored algorithms is linear in the number of added edges. However, tailored algorithms cannot prevent exponential times in settings where the original algorithm is inefficient.}},
  author       = {{Bossek, Jakob and Neumann, Frank and Peng, Pan and Sudholt, Dirk}},
  issn         = {{0178-4617}},
  journal      = {{Algorithmica}},
  keywords     = {{Dynamic optimization, Evolutionary algorithms, Running time analysis}},
  number       = {{10}},
  pages        = {{3148–3179}},
  title        = {{{Time Complexity Analysis of Randomized Search Heuristics for the Dynamic Graph Coloring Problem}}},
  doi          = {{10.1007/s00453-021-00838-3}},
  volume       = {{83}},
  year         = {{2021}},
}

@article{19011,
  author       = {{Degener, Bastian and Gehweiler, Joachim and Lammersen, Christiane}},
  issn         = {{0178-4617}},
  journal      = {{Algorithmica}},
  number       = {{3}},
  pages        = {{562--584}},
  title        = {{{Kinetic Facility Location}}},
  doi          = {{10.1007/s00453-008-9250-7}},
  volume       = {{57}},
  year         = {{2010}},
}

@article{35857,
  author       = {{Blömer, J.}},
  issn         = {{0178-4617}},
  journal      = {{Algorithmica}},
  keywords     = {{Applied Mathematics, Computer Science Applications, General Computer Science}},
  number       = {{1}},
  pages        = {{2--15}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Denesting by Bounded Degree Radicals}}},
  doi          = {{10.1007/s004530010028}},
  volume       = {{28}},
  year         = {{2002}},
}

@inproceedings{18962,
  author       = {{Govindarajan, Sathish and Lukovszki, Tamas and Maheshwari, Anil and Zeh, Norbert}},
  booktitle    = {{Proceedings of the 8th Annual European Symposium on Algorithms (ESA 2000), LNCS}},
  issn         = {{0178-4617}},
  pages        = {{585--614}},
  title        = {{{I/O-Efficient Well-Separated Pair Decomposition and Applications}}},
  doi          = {{10.1007/s00453-005-1197-3}},
  year         = {{2000}},
}

@article{16699,
  author       = {{Meyer auf der Heide, Friedhelm and Oesterdiekhoff, Brigitte and Wanka, Rolf}},
  issn         = {{0178-4617}},
  journal      = {{Algorithmica}},
  pages        = {{413--427}},
  title        = {{{Strongly adaptive token distribution}}},
  doi          = {{10.1007/bf01955042}},
  year         = {{1996}},
}

@article{16700,
  author       = {{Karp, R. M. and Luby, M. and Meyer auf der Heide, Friedhelm}},
  issn         = {{0178-4617}},
  journal      = {{Algorithmica}},
  pages        = {{517--542}},
  title        = {{{Efficient PRAM simulation on a distributed memory machine}}},
  doi          = {{10.1007/bf01940878}},
  year         = {{1996}},
}