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Titel
Bio-inspired optimization techniques using Apache Hadoop / by Christian Gapp
VerfasserGapp, Christian
Betreuer / BetreuerinDurillo, Juan José
Erschienen2015
UmfangVIII, 68 S. : graph. Darst.
HochschulschriftInnsbruck, Univ., Master-Arb., 2015
Datum der AbgabeMärz 2015
SpracheEnglisch
DokumenttypMasterarbeit
Schlagwörter (EN)optimization / bio-inspired / genetic algorithm / hadoop / biohadoop
Schlagwörter (GND)Approximationsalgorithmus / Hadoop
URNurn:nbn:at:at-ubi:1-1753 Persistent Identifier (URN)
Zugriffsbeschränkung
 Das Werk ist frei verfügbar
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Bio-inspired optimization techniques using Apache Hadoop [1.92 mb]
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Zusammenfassung (Englisch)

Problem optimization is a fundamental task encountered everywhere, from everydays life to the most complex science areas. Finding the optimal solution often takes an unreasonable amount of time or computing resources. Therefore, approximation techniques are used to find near-optimal solutions. Bio-inspired algorithms provide such approximation techniques, they mimic existing solutions found in the nature. But even those techniques are sometimes to slow for extensive problems, so they need to be run in parallel.

This master thesis presents a new framework, Biohadoop, to facilitate the implementation and execution of parallelized bio-inspired optimization techniques on Apache Hadoop. Its usefulness is demonstrated by the implementation and performance evaluation of two bio-inspired optimization algorithms.