constraint

Limitations of Linear Programming - Linear programming is applicable only to problems where the constraints and objective function are linear i.e., where they can be expressed as equations which represent straight lines. In real life situations, when constraints or objective fun..

Objective Function: The Objective Function is a linear function of variables which is to be optimised i.e., maximised or minimised. e.g., profit function, cost function etc. The objective function may be expressed as a linear expression. Constraints: A linear equation repr..

Draw the graphs x + y = 1 - 0.5 -5y = - 10 Shade the half planes of the constraints x + y 1 (1) -0.5x - 5y -10 (2) Note that the origin (0, 0) does not satisfy the inequation (2) hence the required region is the upper half plane. From the graph, it is clear that the intersection of..

Some of the methods of linear programming are: The Graphical Method The Analytical Method The Simplex Method In the graphical method, the constraints are actually drawn as straight lines and the optimal solution is found. This method is explained in detail later. The graphical method is n..

Suppose the LPP is to Optimize Z = ax + by subject to the constraints This method of optimization involves the following meth..

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 q..

. The required exposure to sunlight and the right temperature determines the healthy growth of the plant and ensures a good yield. Developing varieties insensitive to these factors will help in overcoming these constraints. Then these crops can be grown in areas, which might not have been..

So far we have learnt how to construct a mathematical model for a linear programming problem. If we can find the values of the decision variables x 1 , x 2 , x 3 , ..... x n , which can optimise (maximize or minimize) the objective function Z, then we say that these values of x i are the optimal so..

Corresponding to each constant, we obtain a shaded region. The intersection of all these shaded regions is the feasible region or feasible solution of the LPP. Let us find the feasible solution for the problem of a decorative item dealer whose LPP is to maximise profit function. Z = 50x + 18y .....

Solve the following LPP graphically using ISO- profit method. maximize Z =100 + 100y. Subject to the constraints ..