6. Building and Solving Stochastic Linear Programming Models with SLP-IOR

P. Kall, J. Mayer
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引用次数: 19

Abstract

The goal of this chapter is to describe the capabilities and the usage of SLP–IOR, our interactive model management system for stochastic linear programming (SLP). The main features of SLP–IOR are the following: the system is intended to support the entire life cycle of a model, including model formulation, analysis of the model instance, solving it, and analyzing the solution. A main design characteristic is keeping connection to an algebraic modeling system; we have chosen GAMS (Brooke, Kendrick, and Meeraus 1992, Brooke et al. 1998). This approach has the following advantages: on the one hand, the powerful general–purpose solvers connected to GAMS are available for solving deterministic equivalents of SLP problems. On the other hand, deterministic LP’s formulated in the algebraic modeling language of GAMS can be imported into SLP–IOR for the purpose of developing stochastic variants of these. However, the usage of GAMS is optional; with the exception of the above–mentioned GAMS–related features, SLP–IOR can be fully utilized without having access to GAMS.
6. 用SLP-IOR建立和求解随机线性规划模型
本章的目标是描述我们的随机线性规划(SLP)交互式模型管理系统SLP - ior的功能和使用。SLP-IOR的主要特点如下:该系统旨在支持模型的整个生命周期,包括模型制定、模型实例分析、求解和分析解决方案。设计的主要特点是与代数建模系统保持联系;我们选择了GAMS (Brooke, Kendrick, and Meeraus 1992, Brooke et al. 1998)。这种方法有以下优点:一方面,连接到GAMS的强大的通用求解器可用于解决SLP问题的确定性等价。另一方面,用GAMS的代数建模语言表述的确定性LP可以导入到SLP-IOR中,用于开发这些LP的随机变体。但是,GAMS的使用是可选的;除了上述与GAMS相关的特性外,SLP-IOR可以在不访问GAMS的情况下充分利用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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