Linear Models

In linear models, the target function and all constraint functions are linear functions of the inputs. If a model is represented algebraically, it is easy to identify whether the model is linear: all expressions will be sums of products of constants and variables, where “variables” refer to the adjustable cells. With complex spreadsheet models, it is not always that easy to spot linearity or the lack of it. However, one advantage of Evolver (and RISKOptimizer) is that a model does not need to be designated linear. The applications will figure it out.

Linear models have been fairly easy to solve since the advent of computers and the invention by George Dantzig of the simplex method. A simple linear model can be solved most quickly and accurately with a linear programming algorithm. Evolver can solve linear models (with no uncertainty) efficiently. The Industrial version can handle an unlimited number of variables and constraints