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Linear programming problems consist of some linear equalities or inequalities with variables in degree one only. These are useful mathematical tools for computing the most favorable outcome in various situations. Whilst the variables set the agenda; the equalities and inequalities act as the boundary lines or constraints. The constraints provide a specific valid region for the problem to operate within which helps in optimization. Solving such problem provides the user with a suitable point within the constraints or so formed polyhedron on graph, where the value of a given function is either lowest or highest. These problems are essentially used in businesses and in judging economic aspects. Companies use them for solving problems related to labor, profit, transportation etc. These problems are solved using graphical methods. Graphical Method Of Solving Linear Programming Problem Assignment Help shall highlight the steps involved in solving these problems.
Steps Used In Graphical Method Of Solving
The different steps involved in graphical method of solving linear programming problem explained in Graphical Method Of Solving Linear Programming Problem Assignment Help are
• Deciding the variables: The variables for the situation should be so chosen that they completely contemplate the important decision that needs to be taken. Faulty picking of variables shall not lead to the desired results. For better understanding of subsequent methods, refer to Graphical Method Of Solving Linear Programming Problem Assignment Help.
• Objective function: Objective function in a linear programming problem is the aim that requires to be fulfilled. It is represented by another variable which hasn’t already been used. This might be the desired profit or cost for a business transaction.
• Constraint analysis: The limitations might be multiple, within whose framework, the problem needs solving. Such limitations are then plotted on a graph to represent the problem in a polyhedron. The signs of the variables must be specified. Whether or not they can have positive and negative values needs to be decided. For more details, refer to Graphical Method Of Solving Linear Programming Problem Assignment Help.
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• Obtaining feasible region: After the constraints are set, the feasible region is obtained by collaborating the signs of variables with the limitations. This region shall contain the solution for the problem. Any point within the region or on the boundary of the polyhedron could be a viable solution.
• Obtaining the solution: This is done by graphing lines such that every point on the line has the same value for the objective function. These parallel lines so formed could be isocost lines or isoprofit lines. Whilst isocost lines are for minimizing, isoprofit lines are for maximizing. For this, a value for objective function is chosen and the X, Y intercepts are calculated.
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