Modeling and Solving Linear Programming with R

Citation

Sallan, Jose M.; Lordan, Oriol; Fernandez, Vicenc (2015). Modeling and Solving Linear Programming with R. Omniascience.

Abstract

Linear programming is one of the most extensively used techniques in the toolbox of quantitative methods of optimization. One of the reasons of the popularity of linear programming is that it allows to model a large variety of situations with a simple framework. Furthermore, a linear program is relatively easy to solve. The simplex method allows to solve most linear programs efficiently, and the Karmarkar interior-point method allows a more efficient solving of some kinds of linear programming. The power of linear programming is greatly enhanced when came the opportunity of solving integer and mixed integer linear programming. In these models all or some of the decision variables are integers, respectively.

In this book we provide a brief introduction to linear programming, together with a set of exercises that introduce some applications of linear programming. We will also provide an introduction to solve linear programming in R. For each problem a possible solution through linear programming is introduced, together with the code to solve it in R and its numerical solution.

Availability

Please see Omniascience website for details, and the repository containing the code used in the book.

Also available through UPCommons in this direction.