Q.Objective function of L.P.P. is _______. A) a constraint
B) a function to be maximized or minimized
C) a relation between the decision variables
D) equation of a straight line

A Linear Programming Problem (L.P.P.) is the problem of maximizing or minimizing a linear function, called the objective function, subject to a set of linear constraints (equations or inequations) on the variables. 'Linear' means every expression involved uses the variables only to the first power — no squares, products of variables, or other non-linear terms. The chapter defines four key terms: (1) Decision variables — the unknown quantities the problem asks us to choose (for example, how many units of two products to manufacture); (2) Objective function — the linear function of the decision variables that is to be optimized, typically representing total profit (to maximize) or total cost (to minimize); (3) Constraints — the conditions, expressed as linear equations or inequations, that restrict the values the decision variables may take (for example, a limited number of machine-hours or a minimum nutrient requirement); (4) Non-negativity constraints — the natural restriction that decision variables cannot be negative (e.g. you cannot manufacture $-3$ units of a product), written as $x\ge0,\ y\ge0$. This chapter restricts itself to L.P.P.s in at most two decision variables, always including the non-negativity constraints, which is exactly what makes the graphical (two-dimensional) method of solving them possible.