2. INTRODUCTION
Linear programming is a mathematical technique used to find the best possible solution in allocating
limited resources (constraints) to achieve maximum profit or minimum cost by modelling linear
relationships.
Model formulation steps :
• Define the decision variables
• Construct the objective function
• Formulate the constraints
• Find the feasible solution
• Calculate the value of the objective function at each of the vertices of feasible solution area to
determine which of them has the maximum or minimum values
3. MODEL COMPONENTS
Decision variables – mathematical symbols representing levels of activity of a firm.
Objective function – a linear mathematical relationship describing an objective of the firm, in terms of
decision variables - this function is to be maximized or minimized.
Constraints – requirements or restrictions placed on the firm by the operating environment, stated in
linear relationships of the decision variables.
Parameters – numerical coefficients and constants used in the objective function and constraints.
4. LP MODEL FORMULATION
Two brands of fertilisers available: SuperGro & CropQuick
Field requires at least 16 kgs of nitrogen and 24 kgs of phosphate
SuperGro costs ₹6 per bag and CropQuick costs ₹3 per bag
SuperGro has 2 kgs of nitrogen & 4 kgs of phosphate
CropQuick has 4 kgs of nitrogen & 3 kgs of phosphate
Problem: How much of each brand to buy to minimize total cost of fertiliser ?
Brand Nitrogen Phosphate
SuperGro 2 4
CropQuick 4 3
5. Decision Variables
x = No. of bags of SuperGro
y = No. of bags of CropQuick
Objective Function
Minimize, z = 6x + 3y
Constraints
2x + 4y >= 16 (nitrogen)
4x + 3y >= 24 (phosphate)
x, y >= 0 (non-negativity constraint)
8. Optimum Solution
Points Z
A (0,8) 24
B (4.8,1.6) 33.6
C (8,0) 48
z = 6x + 3y
So, 8 kgs of CropQuick should be bought to
minimise total cost of fertiliser.