The present section serves the purpose of building your vocabulary
of the terms frequently employed in the description of Linear Programming
Models.
 Linear Function
A linear function contains terms each of which is composed of only
a single, continuous variable raised to (and only to) the power of 1.
Objective Function
It is a linear function of the decision variables expressing the objective
of the decision-maker. The most typical forms of objective functions
are: maximize f(x) or minimize f(x).
Decision Variables
These are economic or physical quantities whose numerical values indicate
the solution of the linear programming problem. These variables are
under the control of the decision-maker and could have an impact on
the solution to the problem under consideration. The relationships among
these variables should be linear.
Constraints
These are linear equations arising out of practical limitations. The
mathematical forms of the constraints are:
f(x) ³ b or f(x) £
b or f(x) = b
Feasible
Solution
Any non-negative solution which satisfies all the constraints is known
as a feasible solution. The region comprising all feasible solutions
is referred to as feasible region.
Optimal
Solution
The solution where the objective function is maximized or minimized
is known as optimal solution.
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