TDMA Time Slot and Turn Optimization with Evolutionary Search Techniques

In this paper we present arithmetic real-coded variation operators tailored for time slot and turn optimization on TDMA-scheduled resources with evolutionary algorithms. Our operators implement a heuristic strategy to converge towards the solution space and are able to escape local minima. Furthermo...

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Veröffentlicht in:Design, Automation and Test in Europe S. 312 - 317
Hauptverfasser: Hamann, Arne, Ernst, Rolf
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: Washington, DC, USA IEEE Computer Society 07.03.2005
IEEE
Schriftenreihe:ACM Conferences
Schlagworte:
Biological cells
Communication networks
Computer networks
Computer systems organization > Architectures > Distributed architectures
Computing methodologies > Artificial intelligence > Search methodologies > Heuristic function construction
Design optimization
Digital arithmetic
Evolutionary computation
Genetic mutations
Legged locomotion
Mathematics of computing > Information theory
Mathematics of computing > Information theory > Coding theory
Networks > Network protocols
Security and privacy > Cryptography > Mathematical foundations of cryptography
Space exploration
Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis > Scheduling algorithms
Theory of computation > Design and analysis of algorithms > Data structures design and analysis > Sorting and searching
Theory of computation > Design and analysis of algorithms > Online algorithms > Online learning algorithms > Scheduling algorithms
Theory of computation > Theory and algorithms for application domains > Machine learning theory > Reinforcement learning > Sequential decision making
Time division multiple access
ISBN:9780769522883, 0769522882
ISSN:1530-1591
Online-Zugang:Volltext
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Abstract In this paper we present arithmetic real-coded variation operators tailored for time slot and turn optimization on TDMA-scheduled resources with evolutionary algorithms. Our operators implement a heuristic strategy to converge towards the solution space and are able to escape local minima. Furthermore, we explicitly separate the variation of the admitted loads and the turn-length in order to give the designer increased control over the optimization process. Experimental results show that our variation operators have advantages over string-coded binary variation operators which are frequently used to solve continuous optimization problems.
AbstractList In this paper we present arithmetic real-coded variation operators tailored for time slot and turn optimization on TDMA-scheduled resources with evolutionary algorithms. Our operators implement a heuristic strategy to converge towards the solution space and are able to escape local minima. Furthermore, we explicitly separate the variation of the admitted loads and the turn-length in order to give the designer increased control over the optimization process. Experimental results show that our variation operators have advantages over string-coded binary variation operators which are frequently used to solve continuous optimization problems.
In this paper we present arithmetic real-coded variation operators tailored for time slot and turn optimization on TDMA-scheduled resources with evolutionary algorithms. Our operators implement an heuristic strategy to converge towards the solution space and are able to escape local minima. Furthermore, we explicitly separate the variation of the admitted loads and the turn-length in order to give the designer increased control over the optimization process. Experimental results show that our variation operators have advantages over string-coded binary variation operators which are frequently used to solve continuous optimization problems.
Author Ernst, Rolf
Hamann, Arne
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  organization: Technical University of Braunschweig, Germany
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SubjectTerms Biological cells
Communication networks
Computer networks
Computer systems organization -- Architectures -- Distributed architectures
Computing methodologies -- Artificial intelligence -- Search methodologies -- Heuristic function construction
Design optimization
Digital arithmetic
Evolutionary computation
Genetic mutations
Legged locomotion
Mathematics of computing -- Information theory
Mathematics of computing -- Information theory -- Coding theory
Networks -- Network protocols
Security and privacy -- Cryptography -- Mathematical foundations of cryptography
Space exploration
Theory of computation -- Design and analysis of algorithms -- Approximation algorithms analysis -- Scheduling algorithms
Theory of computation -- Design and analysis of algorithms -- Data structures design and analysis -- Sorting and searching
Theory of computation -- Design and analysis of algorithms -- Online algorithms -- Online learning algorithms -- Scheduling algorithms
Theory of computation -- Theory and algorithms for application domains -- Machine learning theory -- Reinforcement learning -- Sequential decision making
Time division multiple access
Title TDMA Time Slot and Turn Optimization with Evolutionary Search Techniques
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