Simulation and Optimization : Proceedings of the International Workshop on Computationally Intensive Methods in Simulation and Optimization held at the International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austr

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ISBN 10: 3540549803 / ISBN 13: 9783540549802

Published by Springer Berlin Heidelberg, 1992

About this Item

Zustand: Sehr gut | Seiten: 180 | Sprache: Englisch | Produktart: Bücher.

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Bibliographic Details

• Title: Simulation and Optimization : Proceedings of the International Workshop on Computationally Intensive Methods in Simulation and Optimization held at the International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austr
• Publisher: Springer Berlin Heidelberg
• Publication Date: 1992
• Language: English
• ISBN 10: 3540549803
• ISBN 13: 9783540549802
• Binding: Soft cover
• Condition: Sehr gut

About this title

Synopsis

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.