Question $1(1$ point$)$

The feasible solution space in linear programming is the set of all possible combinations of decision variables, regardless of whether they satisfy the given constraints.

$$ True

$$ False

Question $2(1$ point$)$

Parameters in an LP model are variables whose values change as the optimization process progresses.

True

$$ False

Question $3(1$ point$)$

Constraints in linear programming only come in the form of "less than or equal to$"(s)$ and "equal to$"(=)$ relationships.

True

False

Question $4(1$ point$)$

Decision variables in linear programming represent fixed values that cannot be adjusted to optimize the objective function.

$$ True

False