LINEAR PROGRAMMING

The corner point method for bounded feasible region comprises of the following steps I. When the feasible region is bounded, M and m are the maximum and minimum values of Z. II. Find the feasible region of the linear programming problem and determine its corner points. Ill. Evaluate the objective function Z = ax + by at each corner point. Let M and m respectively be the largest and smallest values of these points. The correct order of these above steps is

A dealer deals in two items A and B He has Rs. 15000 to invest and a space to store almost 80 pieces Item A costs him Rs 300 and item B costs him Rs. 150 He can sell items A and B at profits of Rs 40 and Rs 25 respectively Assuming that he can sell all that he buys formulate the above as a linear programming prioblem for maximum profit and solve it graphically

Mathematical Formulation of Linear programing problem(Example)

Out of the following frame of linear programmed Instruction,which of the following frame is exactly related with teaching-learning context?

If a young man rides his motorcycle at 25 km/hr, he has to spend 2 per kilometer on petrol if per he rides it at a faster speed of 40 km/hr the petrol cost increases to 5 per kilometer.He has 100 to spend on petrol and wishes to find the maximum distance he can travel within one hours. Express this as a linear programming problem and then solve it.

If a young man drives his car at 40 km per hour, he has to spend ₹ 5 per km on petrol, if he drives it at a slower speed of 25 km per hour, the petrol cost decreases to ₹ 2 per km. He has ₹ 100 to spend on petrol and wishes to find thhe maximum distance he can travel within one hour.Express this as a linear programming problem and then solve it.

Food F_1 contains 5 units of vitamin A and 6 units of vitamin B per gram and costs 20 p/gm. Food F_2 contains 8 units of vitamin A and 10 units of vitamin B per gram and costs 30 p/gm. The daily requirements of A and B are at least 80 and 100 units respectively. Formulate the problem as a linear programming problem to minimize cost.