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Objektorientierte und verteilte Lösung von Optimierungsproblemen pp 37–71Cite as

Optimierung und Parallelverarbeitung auf Workstation-Clustern

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Part of the book series: Beiträge zur Wirtschaftsinformatik ((WIRTSCH.INFORM.,volume 25))

Zusammenfassung

Optimierung bedeutet, „unter mehreren möglichen Realisationen eine Alternative zugunsten der besseren oder besten — nach Leibniz: optimalen — herbeizuführen“ [Schw77, S. 5]. Das Ermitteln dieser optimalen Lösung ist ein aufwendiger Prozeß mit einem hohen Rechenzeitbedarf. Die multidisziplinäre Optimierung (Koppelung mehrere Analysemethoden mit der Optimierung) zählt aufgrund der verwendeten Programmsysteme zu den Aufgabenstellungen des „wissenschaftlichen Höchstleistungsrechnens“ (High Performance Scientific Computing — HPSC [SOF92]). Sie stellt Anforderungen von hundert Megaflops und mehr an die verfügbaren Rechnerressourcen. Wie neuere Ansätze zur multidisziplinären Optimierung [Cram94, Schn94] zeigen, sind gerade diese Probleme aufgrund ihrer inhärenten Struktur für die Berechnung auf Workstation-Qustern geeignet. Mit Dekompositionstechniken lassen sich Zerlegungen erreichen, die von Systemen mit geringeren Ressourcen verteilt bearbeitet werden können. In die Dekomposition und Verteilung eines Problems auf einen Cluster sowie die Kontrolle des Lösungsfindungsprozesses mit einem klassenbasierten Ansatz soll hier eingeführt werden.

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Brüggemann, F.J. (1997). Optimierung und Parallelverarbeitung auf Workstation-Clustern. In: Objektorientierte und verteilte Lösung von Optimierungsproblemen. Beiträge zur Wirtschaftsinformatik, vol 25. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-51734-1_3

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