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Herausgeber: 
  • Georg Pflug
  • Ulrich Dieter
  • Simulation and Optimization: Proceedings of the International Workshop on Computationally Intensive Methods in Simulation and Optimization held at the 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

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    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  Januar 1992  
    Genre:  EDV / Informatik 
     
    Communication / discreteeventsystems / Management# Entscheidungstheorie / Optimierung / Optimization / Randomnumbers / Simulation / stochasticoptimization
    ISBN:  9783540549802 
    EAN-Code: 
    9783540549802 
    Verlag:  Springer 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 244 mm / B 170 mm / D 11 mm 
    Gewicht:  322 gr 
    Seiten:  180 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This volume contains selected papers presented at the "International Workshop on Computationally Intensive Methods in Simulation and Op­ th th timization" held from 23 to 25 August 1990 at the International Institute for Applied Systems Analysis (nASA) in La~enburg, Austria. The purpose of this workshop was to evaluate and to compare recently developed methods dealing with optimization in uncertain environments. It is one of the nASA's activities to study optimal decisions for uncertain systems and to make the result usable in economic, financial, ecological and resource planning. Over 40 participants from 12 different countries contributed to the success of the workshop, 12 papers were selected for this volume. Prof. A. Kurzhanskii Chairman of the Systems and Decision Sciences Program nASA Preface Optimization in an random environment has become an important branch of Applied Mathematics and Operations Research. It deals with optimal de­ cisions when only incomplete information of t.he future is available. Consider the following example: you have to make the decision about the amount of production although the future demand is unknown. If the size of the de­ mand can be described by a probability distribution, the problem is called a stochastic optimization problem.

      



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