# Properties And Basic Assumptions Of Linear Programming Pdf

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## Linear programming

Speci cation The following assumptions must be considered when using linear regression analysis. We have now validated that all the Assumptions of Linear Regression are taken care of and we can safely say that we can expect good results if we take care of the assumptions. The expected value of the errors is always zero 4. Here is a simple definition.

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Assumptions of Linear Programming 1. Conditions of Certainty. It means that numbers in the objective and constraints are known with certainty and do change during the period being studied. Linearity or Proportionality. We also assume that proportionality exits in the objective and constraints. This means that if production of 1 unit of product uses 6 hours, then making 10 units of that product uses 60 hours of the resources.

Now that you have seen how some simple problems can be formulated and solved as linear programs, it is useful to reconsider the question of when a problem can be realistically represented as a linear programming problem. A problem can be realistically represented as a linear program if the following assumptions hold:.

Linear programming , mathematical modeling technique in which a linear function is maximized or minimized when subjected to various constraints. This technique has been useful for guiding quantitative decisions in business planning, in industrial engineering , and—to a lesser extent—in the social and physical sciences. The solution of a linear programming problem reduces to finding the optimum value largest or smallest, depending on the problem of the linear expression called the objective function. The basic assumption in the application of this method is that the various relationships between demand and availability are linear; that is, none of the x i is raised to a power other than 1. In order to obtain the solution to this problem, it is necessary to find the solution of the system of linear inequalities that is, the set of n values of the variables x i that simultaneously satisfies all the inequalities. The objective function is then evaluated by substituting the values of the x i in the equation that defines f.

## Assumptions of Linear Programming

We used the simplex method for finding a maximum of an objective function. The procedure can be explained in the following steps Step 1 Formulate the linear programming problem by identifying the decision variables the objective function and the constraints. LP A graphical method for solving linear programming problems is outlined below. Actually vertices are solutions of two equations.

Linear programming is based on four mathematical assumptions. An assumption is a simplifying condition taken to hold true in the system being analyzed in order to render the model mathematically tractable solvable. The first three assumptions follow from a fundamental principle of LP: the linearity of all model equations. This applies to constraint inequalities as well, since the addition of slack and surplus variables convert all inequalities into equations.

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*Quantitative Analysis for Management, 11e Render Chapter 7 Linear Programming Models: Graphical and Computer Methods 1 Management resources that need control include machinery usage, labor volume, money spent, time used, warehouse space used, and material usage. B must satisfy all of the problem's constraints simultaneously. C need not satisfy all of the constraints, only the non-negativity constraints.*

This paper will cover the main concepts in linear programming, including For instance, several assumptions are implicit in linear programing problems. problem. The vector x is a vector of solutions to the problem, b is the right- ables as binary, so ensuring this property of yk would not be an obstacle in.