UNIT: II - Greedy Method

FEASIBLE SOLUTION,OPTIMAL SOLUTION AND OBJETIVE FUNCTION:

A) Feasible Solution:

A solution (set of values for the decision variables) for which all of the constraints in the Linear Programming problem are satisfied is called a feasible solution. It is subset of a solution which satisfies restrictions applied to the problem Linear programming (LP) (also called linear optimization) is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships.

B) Optimal Solution:

An optimal solution is a feasible solution where the objective function reaches its maximum (or minimum) value – for example, the most profit or the least cost. A globally optimal solution is one where there are no other feasible solutions with better objective function values. A locally optimal solution is one where there are no other feasible solutions “in the vicinity” with better objective function values A solution that satisfies all the constraints of a linear programming with high profit and low cost is known as optimal solution.

C) Objective Function:

A function that is used to determine a good solution for optimizing problem is known as objective function.

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