Algorithmics in Dynamic Environments
A special issue of Algorithms (ISSN 1999-4893).
Deadline for manuscript submissions: closed (15 December 2019) | Viewed by 503
Special Issue Editor
Interests: complexity theory; worst-case complexity of exact algorithms for NP-hard problems; approximation of NP-hard optimization problems; polynomial approximability; moderately exponential; subexponential and parameterized approximation; algorithmics in dynamic environments
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Special Issue Information
Dear Colleagues,
Dynamic environments in complexity theory describes situations where either the instance is unknown a priori, or it changes with time (data and the relations between them), or every datum is finally present with some probability. There are three well-known dynamic optimization models, namely:
—Online algorithms (where the future input is unknown and is revealed datum by datum, or by sets of data)
—Probabilistic optimization (where the presence of a datum in a final instance has some probability)
—Reoptimization models (where an initial instance of a combinatorial problem together with a solution are given, and a subset of the initial data disappears)
For all of these models, the objective is to compute the best possible solution for the final instance.
For this Special Issue, we invite submissions of articles that describe recent advances in the design and analysis of algorithms handling problems in dynamic environments as described above, that to the proposal of other dynamic models.
Both original research papers and surveys are welcome.
Prof. Dr. Vangelis Th. Paschos
Guest Editor
Manuscript Submission Information
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