Randomized priority algorithms

Borodin, Nielsen and Rackoff  [13] introduced the class of priority algorithms as a framework for modeling deterministic greedy-like algorithms. In this paper we address the effect of randomization in greedy-like algorithms. More specifically, we consider approximation ratios within the context of r...

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Veröffentlicht in:Theoretical computer science Jg. 411; H. 26; S. 2542 - 2558
Hauptverfasser: Angelopoulos, Spyros, Borodin, Allan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Elsevier B.V 06.06.2010
Elsevier
Schlagworte:
Algorithmics. Computability. Computer arithmetics
Algorithms
Applied sciences
Approximation
C (programming language)
Computer Science
Computer science; control theory; systems
Computer simulation
Computer systems performance. Reliability
Data Structures and Algorithms
Exact sciences and technology
Facility location
Greedy algorithms
Makespan scheduling
Mathematical analysis
Miscellaneous
Optimization
Priorities
Randomization
Randomized approximation algorithms
Scheduling
Software
Theoretical computing
Greedy algorithms
Facility location
Randomized approximation algorithms
Makespan scheduling
Approximation
Computer theory
Priority
Optimization method
Scheduling
Makespan
Approximation algorithm
Modeling
Location problem
Case study
Randomization
Greedy algorithm
Deterministic algorithms
ISSN:0304-3975, 1879-2294
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Beschreibung
Zusammenfassung:Borodin, Nielsen and Rackoff  [13] introduced the class of priority algorithms as a framework for modeling deterministic greedy-like algorithms. In this paper we address the effect of randomization in greedy-like algorithms. More specifically, we consider approximation ratios within the context of randomized priority algorithms. As case studies, we prove inapproximation results for two well-studied optimization problems, namely facility location and makespan scheduling.
Bibliographie:ObjectType-Article-1
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ISSN:0304-3975
1879-2294
DOI:10.1016/j.tcs.2010.03.014