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By Professor Dr. Wolfgang Domschke, Professor Dr. Andreas Drexl (auth.)

Dieses Buch ist aus Vorlesungen zur Einf?hrung in Operations study, die die Autoren gehalten haben, entstanden. Vordringliches Ziel ist nicht die Darstellung aktueller Forschungsergebnisse, sondern eine didaktisch gute Aufbereitung des Stoffes und die Vermittlung der Grundlagen dieser jungen Wissenschaftsdisziplin. Die Verfahren werden algorithmisch beschrieben und an Beispielen verdeutlicht. Das Buch ist auch zum Selbststudium geeignet. Im einzelnen behandelt der textual content die lineare Optimierung, Graphentheorie, lineare Optimierungsprobleme mit spezieller Struktur, Netzplantechnik, ganzzahlige und kombinatorische Optimierung, dynamische Optimierung, nichtlineare Optimierung, Warteschlangentheorie, Simulation.

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1 J spielt J lJ b1 b2 e. -1 a1 2 3 2 a2 3 4 3* e. 3* 4 J Tab. 23 Tab. a.

19) mit 4 die obere Schranke 36: F(x l ,x 2) = 6x I + 4x 2 ~ 12x I + 4x 2 ~ 36 Schärfere obere Schranken erhält man in der Regel durch Linearkombination aller Nebenbedingungen (mit Ausnahme der Nichtnegativitätsbedingungen) eines LOPs. 20 des Ubungsbuchs Domschke et al. (1995). 36 Kapitel 2: Lineare Optimierung Ein Vergleich der Koeffizienten von Xl bzw. x2 liefert die Bedingungen: 9 6X l ~ (w l + 3w2) ·X l bzw. 24) ~ Man überlegt sich dazu jedoch, daß die Koeffizienten w1 und w2 nicht beliebig gewählt werden dürfen.

277). Da sich B in jeder Iteration jedoch nur in einer Spalte, der Pivotspalte, verändert, kann diese Berechnung entsprechend vereinfacht werden. 18 in Dornschke et al. (1995). Der revidierte Simplex-Algorithmus ist vor allem dann besonders effizient, wenn m wesentlich kleiner als n ist. Beispiel: Wir wollen die Vorgehensweise anhand unseres Gärtnerproblems aus Kap. 2 veranschaulichen. Das Anfangstableau Ä ist nochmals in Tab. 13 wiedergegeben. BV Xl x2 x3 x3 x4 x5 1 6 1 9 1 1 F -1 -2 0 x4 x5 b.

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