Introduction to Stochastic Programming, Second Edition
Introduction to Stochastic Programming, Second Edition
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DOI：
10.1007/978-1-4614-0237-4
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发表时间：
2011-01-01
期刊：
影响因子：
--
通讯作者：
Louveaux, Francois
中科院分区：
文献类型：
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作者：
Birge, John R.;Louveaux, Francois
随机规划的目的是在涉及不确定数据的问题中找到最优决策。这一领域目前正在迅速发展，许多学科的贡献，包括运筹学，数学和概率。与此同时，它现在被应用于从农业到财务规划，从工业工程到计算机网络等各种各样的学科。本教科书提供了随机规划的第一门课程，适合具有线性规划、初等分析和概率基础知识的学生。作者的目的是提出一个广泛的概述的主题和方法的主题。它的主要目标是帮助学生培养一种直觉，了解如何将不确定性建模为数学问题，不确定性变化给决策过程带来了什么，以及什么技术有助于管理解决问题时的不确定性。在这个广泛更新的新版本中，有更多关于方法和示例的材料，包括离散变量的几种新方法，建模和蒙特卡洛抽样方法中风险度量的新结果，与其他方法的关系的新章节，包括近似动态规划，鲁棒优化和在线方法。这本书是高度说明与章节摘要和许多例子和练习。学生，研究人员和从业人员在运筹学和优化领域将发现它特别感兴趣。第一版回顾：“对建模问题的讨论，用于说明材料的大量示例以及覆盖范围的广度使《随机编程导论》成为该领域的理想教科书。“（Interfaces，1998年）
The aim of stochastic programming is to find optimal decisions in problems which involve uncertain data. This field is currently developing rapidly with contributions from many disciplines including operations research, mathematics, and probability. At the same time, it is now being applied in a wide variety of subjects ranging from agriculture to financial planning and from industrial engineering to computer networks. This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability. The authors aim to present a broad overview of the main themes and methods of the subject. Its prime goal is to help students develop an intuition on how to model uncertainty into mathematical problems, what uncertainty changes bring to the decision process, and what techniques help to manage uncertainty in solving the problems. In this extensively updated new edition there is more material on methods and examples including several new approaches for discrete variables, new results on risk measures in modeling and Monte Carlo sampling methods, a new chapter on relationships to other methods including approximate dynamic programming, robust optimization and online methods. The book is highly illustrated with chapter summaries and many examples and exercises. Students, researchers and practitioners in operations research and the optimization area will find it particularly of interest. Review of First Edition:" The discussion on modeling issues, the large number of examples used to illustrate the material, and the breadth of the coverage make'Introduction to Stochastic Programming'an ideal textbook for the area."(Interfaces, 1998)