Respuesta :
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.
Statement that cannot be regarded as a true statement in this question is B: feasible solution satisfies all constraints.
- For an infeasible solution all constraints can be violated, then option A is correct.
- A feasible solution point doesn't requires to lie on the boundary of the feasible region and in feasible solution, nit all constraints are satisfied. An optimal solution can also satisfies all constraints.
Therefore, option B is correct.
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