#### General form of LLP

Introduction to Linear Programming

A linear form is made a mathematical expression of the type a1x1 + a2x2 + .... + anxn, where a1, a2, ..., an are constant and x1, x2 ... xn are variable. The word Programming means the procedure of determining a particular program or plan of action. So Linear Programming (LP) is one of the highly significant optimization (maximization / minimization) techniques which are developed in the field of Operations Research (OR).

The methods applied for answering a linear programming problem are fundamentally simple problems; an answer can be achieved by a set of simultaneous equations. Though an exclusive solution for a set of simultaneous equations in n-variables (x1, x2 ... xn), at least one of them is non-zero, can be obtained if there are precisely n relations. When the number of relations is more than or less than n then a unique solution does not exist but several trial solutions can be found.

In different practical conditions, the queries are seen in which the number of relations is not equal to the number of the number of variables and a lot of relations are in the form of inequalities (≤ or ≥) to maximize or minimize a linear function of the variables subject to like conditions. These problems are called as Linear Programming Problem (LPP).

General form of LPP

We develop a mathematical model for common problem of allocating resources to different activities. In particular, this model is to choose the values for x1, x2 ... xn in order to maximize or minimize

Z = c1x1 + c2x2 +.............+cnxn

subject to limitations or restrictions

a11x1 + a12x2 + .............+a1nxn (≤ or ≥) b1

a21x1 + a22x2 + ...........+a2nxn (≤ or ≥) b2

.

.

.

am1x1 + am2x2 + ..........+amnxn (≤ or ≥) bm

and

x1 ≥ 0, x2 ≥ 0,..., xn ≥ 0

Where

Z = value of on the whole measure of performance

xj = level of activity (for j = 1, 2, ..., n)

cj = increase in Z that would result from each unit enhance in level of activity j

bi = amount of resource i that is available for allocation to activities (for i = 1,2, ..., m)

aij = amount of resource i used by each unit of activity j

 Resource Resource usage per unit of activity Amount of resource available Activity 1     2 ..........................  n 1 2 . . . m a11 a12 .........................a1n a21 a22 .........................a2n . . . am1 am2 .........................amn b1 b2 . . . bm Contribution to Z per unit of activity c1  c2 .............................cn

Data needed for LP model

• The level of activities x1, x2.........xn are known as decision variables.
• The values of the cj, bi, aij (for i=1, 2 ... m and j=1, 2 ... n) are the input constants for the model. They are known as parameters of the model.
• The function being maximized or minimized Z = c1x1 + c2x2 +.... +cnxn is known as objective function.
• The restrictions are normally referred to as constraints. The constraint ai1x1 + ai2x2 ... ainxn are at times knownas functional constraint (L.H.S constraint). xj ≥ 0 restrictions are referred to as non-negativity constraint.

Assumptions in LPP

Sum of the resources utilized by diverse activities must be equivalent to the total amount of resources used by each activity for all resources collectively or individually.

1. Proportionality

The contribution or participation of each variable in the main function or its usage of the resources is directly proportional to the value of the variable that is if resource accessibility rises by some percentage, then the output will also rise by same percentage

1. Divisibility

The variables are not limited to integer values

1. Finiteness

Variables and constraints are limited in number.

1. Deterministic

Coefficients in the objective function and constraints are totally known and do not vary during the period under study in all the problems taken.

1. Optimality

In LPP, we establish the decision variables in order to optimize the objective function of the LPP.

1. The problem includes only one objective either profit maximization or cost minimization.

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