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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Beschreibung
Zusammenfassung: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.
Bibliographie:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:9780769522883
0769522882
ISSN:1530-1591
DOI:10.1109/DATE.2005.299