Answer:
B. A feasible solution satisfies all constraints.
Explanation:
Linear programming can be explained as a simple technique where we depict complex relationships through linear functions then find the optimum points.
Linear programming is employed for obtaining the foremost optimal solution for a drag with given constraints. In applied mathematics,
real life problem are formulate into a mathematical model. It involves an objective function, linear inequalities with subject to constraints.
Constraints: The constraints are the restrictions or limitations on the decision variables. They usually limit the value of the decision variables.
Hence,
An infeasible solution violates all constraints.
A feasible solution point does not have to lie on the boundary of the feasible region.
An optimal solution satisfies all constraints.
