This document shows how to model two-stage stochastic linear programming problems in a GAMS environment. We will demonstrate using a small example, how GAMS can be used to formulate and solve this model as a large LP or using specialized stochastic solvers such as OSL-SE and DECIS. Finally a tailored implementation of the Benders Decomposition algorithm written in GAMS is used to solve the model.

The FADN (farm accountancy data network) provides farm accountancy data to determine and analyse income of agricultural holdings. The underlying data base has to be prepared for properly assessing the impacts of EU policy changes and market developments on agricultural income. This article presents the FADN data mining tool that reads and converts the given data for analysing the data itself an...

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 ch...

Sustainable energy consumption is a research area of a large interest in last years. New energy-efficient lighting technologies exist, which can significantly reduce household electricity consumption, but their adoption has been slow. A considerable number of international studies show that sustainable development scenarios will be realistic if they involve the human behavior. The paper provide...

Glioblastomas are highly infiltrated by diverse immune cells, including microglia, macrophages, and myeloid-derived suppressor cells (MDSCs). Understanding the mechanisms by which glioblastoma-associated myeloid cells (GAMs) undergo metamorphosis into tumor-supportive cells, characterizing the heterogeneity of immune cell phenotypes within glioblastoma subtypes, and discovering new targets can ...

Bayesian analysis provides a convenient setting for the estimation of complex generalized additive regression models (GAMs). Since computational power has tremendously increased in the past decade it is now possible to tackle complicated inferential problems, e.g., with Markov chain Monte Carlo simulation, on virtually any modern computer. This is one of the reasons why Bayesian methods have be...

GAMS (General Algebraic Modelling System) is a computer language which was originally developed to assist economists at the World Bank in the quantitative analysis of economic policy questions (Meeraus (1983), Brooke, Kendrick and Meeraus (1987)). At the time of its conception and initial development, linear programming (LP) was the standard framework in which market equilibrium models were con...

This document illustrates the Dantzig-Wolfe decomposition algorithm using GAMS.