Question

Define the following:
(i)No solution
(ii) Multiple solutions
(ii) Mixed constraints
(iv) Redundant constraints
(v) Objective function​

Answer 1

Answer:

I . No solution would mean that there is no answer to the equation. It is impossible for the equation to be true no matter what value we assign to the variable. ... Let's look at the following equation: Note that we have variables on both sides of the equation.

II . Multiple solutions of a linear programming problem are solutions each of which maximize or minimize the objective function under Simplex Method.

III . The constraints for the maximization problems all involved inequalities, and the constraints for the minimization problems all involved inequalities. Linear programming problems for which the constraints involve both types of inequali- ties are called mixed-constraint problems.

IV . Redundant constraints are constraints that can be omitted from a system of linear. constraints without changing the feasible region. Implicit equalities are inequality constraints. that can be replaced by equalities without changing the feasible region.

V . in linear programming) the function that it is desired to maximize or minimize.

Answer 2

Step-by-step explanation:

1)The solution x = 0 means that the value 0 satisfies the equation, so there is a solution. “No solution” means that there is no value, not even 0, which would satisfy the equation. ... This is because there is truly no solution—there are no values for x that will make the equation 12 + 2x – 8 = 7x + 5 – 5x true.

2)Multiple solutions of a linear programming problem are solutions each of which maximize or minimize the objective function under Simplex Method.

3)The constraints for the maximization problems all involved inequalities, and the constraints for the minimization problems all involved inequalities. Linear programming problems for which the constraints involve both types of inequali- ties are called mixed-constraint problems.

4)Redundant constraints are constraints that can be omitted from a system of linear. constraints without changing the feasible region. Implicit equalities are inequality constraints. that can be replaced by equalities without changing the feasible region.

5)Objective Function: The objective function in a mathematical optimization problem is the real-valued function whose value is to be either minimized or maximized over the set of feasible alternatives.