These case studies highlight the field of linear programming (LP) from two perspectives.
Simplex Pivot Tools
Developed by George Dantzig in 1947, the simplex method is a general procedure for solving linear programming (LP) problems. The simplex method is an algebraic procedure based on solving systems of equations; it has proved to be very efficient in practice as an algorithm for solving large-scale LPs, even though its worst-case complexity is exponential. Below are links to JavaScript-based simplex pivot tools developed by Robert Vanderbei at Princeton University. Their purpose is to facilitate learning the fundamental ideas behind various versions of the simplex method.
The Diet Problem
The Diet Problem, dating back to the 1930s and the 1940s, presents a LP model for selecting a minimum cost set of foods that will satisfy a set of daily nutritional requirements. This case study includes an interactive tool for building a menu.
Simple Pivot Tool
The Simple Pivot Tool was developed by Robert Vanderbei at Princeton University to solve linear programming (LP) problems.
Advanced Pivot Tool
This Advanced Pivot Tool was developed by Robert Vanderbei at Princeton University to solve linear programming (LP) problems.
Network Simplex Pivot Tool
This pivot tool was developed by Robert Vanderbei at Princeton University to solve network flow problems.