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A seminar talk on “SOLVING LINEAR PROGRAMMING PROBLEM BY GRAPHICAL METHOD” By S K Indrajitsingha M.Sc.

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Presentation on theme: "A seminar talk on “SOLVING LINEAR PROGRAMMING PROBLEM BY GRAPHICAL METHOD” By S K Indrajitsingha M.Sc."— Presentation transcript:

1 A seminar talk on “SOLVING LINEAR PROGRAMMING PROBLEM BY GRAPHICAL METHOD” By S K Indrajitsingha M.Sc

2 Introduction Formation of linear programming problem Solving of linear programming by graphical method conclusion

3 Linear programs are problems that can be expressed in canonical form
Linear Programming:- Linear programming is a method that is used to find a minimum or maximum value for a function. That value is going to satisfy a known set of conditions constraints. Constraints are the inequalities in the linear programming problem. Their solution is graphed as a feasible region, which is a set of points. These points are where the graphs of the inequalities intersect. :      Linear programs are problems that can be expressed in canonical form                                        

4 LP Characteristics:- Feasible Region: The set of points that satisfies all constraints Corner Point Property: An optimal solution must lie at one or more corner points Optimal Solution: The corner point with the best objective function value is optimal

5 Formulation of linear programming problem

6 THERE ARE MAINLY FOUR STEPS IN THE MATHEMATICAL FORMULATION OF LINEAR PROGRAMMING PROBLEM AS A MATHEMATICAL MODEL. WE WILL DISCUSS FORMULATION OF THOSE PROBLEMS WHICH INVOLVE ONLY TWO VARIABLES. *Identify the decision variables and assign symbols x and y to them. These decision variables are those quantities whose values we wish to determine. *Identify the set of constraints and express them as linear equations/inequations in terms of the decision variables. These constraints are the given conditions. *Identify the objective function and express it as a linear function of decision variables. It might take the form of maximizing profit or production or minimizing cost. *Add the non-negativity restrictions on the decision variables, as in the physical problems, negative values of decision variables have no valid interpretation

7 . A DIET IS TO CONTAIN AT LEAST 4000 UNITS OF CARBOHYDRATES, 500 UNITS OF FAT AND 300 UNITS OF PROTEIN. TWO FOODS A AND B ARE AVAILABLE. FOOD A COSTS 2 DOLLARS PER UNIT AND FOOD B COSTS 4 DOLLARS PER UNIT. A UNIT OF FOOD A CONTAINS 10 UNITS OF CARBOHYDRATES, 20 UNITS OF FAT AND 15 UNITS OF PROTEIN. A UNIT OF FOOD B CONTAINS 25 UNITS OF CARBOHYDRATES, 10 UNITS OF FAT AND 20 UNITS OF PROTEIN. FORMULATE THE PROBLEM AS AN LPP SO AS TO FIND THE MINIMUM COST FOR A DIET THAT CONSISTS OF A MIXTURE OF THESE TWO FOODS AND ALSO MEETS THE MINIMUM REQUIREMENTS.

8 LET THE DIET CONTAIN X UNITS OF A AND Y UNITS OF B.
\ Total cost = 2x + 4y THE LPP FORMULATED FOR THE GIVEN DIET PROBLEM IS Minimize Z = 2x + 4y SUBJECT TO THE CONSTRAINTS                                                      

9 Solving linear programming problem by using graphical method

10 There are 7 steps that are used when solving a problem using linear programming.
1. Define the variables. 2. Write a system of inequalities. 3. Graph the system of inequalities. 4. Find the coordinates of the vertices of the feasible region. 5. Write a function to be maximized or minimized. 6. Substitute the coordinates of the vertices into the function. 7. Select the greatest or least result. Answer the problem.

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33 Advantage and Limitation:-
Graphical method to solve Linear Programming problem (LPP) helps to visualize the procedure explicitly. It also helps to understand the different terminologies associated with the solution of LPP. In this class, these aspects will be discussed with the help of an example. However, this visualization is possible for a maximum of two decision variables. Thus, a LPP with two decision variables is opted for discussion. However, the basic principle remains the same for more than two decision variables also, even though the visualization beyond two-dimensional case is not easily possible.

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