Linear programming model Linear Programming can be defined as the problem minimizing of or maximizing a linear function over a convey polyhedron specified by linear and non-negativity constraints. In relatively easy terms linear programming is the optimization of a result based on some set of limitations using a linear mathematical model. Linear Programming is also known as Linear Optimization. Objective The return or cost function to be maximized or minimized is called the objective Constraints In business, it is often desirable to find the production levels that will produce the maximum profit or the minimum cost. The production process can often be described with a set of linear inequalities called constraints. Feasible solution A feasible solution is a solution that satisfies all of the constraints Feasible region The feasible region is the set of all feasible solutions. Optimal solution . The optimal solution is the feasible solution that optimizes the objective Sensitivity analysis This is, in fact, how management science models are used in the business world. They are typically developed to solve a particular problem, but they are then used as a tool to analyze a number of variations of the basic problem. Algebraic model If you are developing an algebraic model, you must derive the correct algebraic expressions. If you are developing a spreadsheet model, the main focus of this book, you must relate all variables with appropriate cell formulas. Spreadsheet model If you are developing a spreadsheet model, the main focus of this book, you must relate all variables with appropriate cell formulas. Infeasibility A perfectly reasonable model can have no feasible solutions because of too many constraints 1. there is a mistake in the model (an input was entered incorrectly, such as a symbol instead of a ) or 2. The problem has been so constrained that there are no solutions left. Decision support system (DSS) that can help them solve problems without having to worry about technical details