Formulating an L.P.P. means translating a real-world word problem into the precise mathematical shape of decision variables, an objective function, and a set of constraints. The chapter gives a fixed three-step working rule: Step 1 — identify the decision variables and assign them symbols such as $x,y$ (or $x_1,x_2$), remembering to introduce the non-negativity constraints $x\ge0,y\ge0$; Step 2 — identify what is to be optimized (usually total profit or total cost) and write it as a linear expression in the decision variables — this is the objective function; Step 3 — identify every resource limit or requirement stated in the problem (machine-hours available, raw material availability, minimum nutrient needs, budget, storage space, etc.) and express each one as a linear inequation. A resource that is available only up to some maximum amount gives a $\le$ constraint (e.g. machine-hours, budget, storage space); a requirement that must be met at least to some minimum level gives a $\ge$ constraint (e.g. minimum nutrients in a diet, minimum strength in a mixture). Data given in a table (one row per resource, one column per product, showing how much of that resource each unit of each product consumes, with the row's availability in the last column) converts directly into one inequation per row. Getting the formulation right is the foundation for everything that follows — an L.P.P. with a formulation error will be solved 'correctly' but will not answer the real question.