any opinion is valid!

I think the simplex technique, a potent approach for solving linear programming issues, maximizes the objective function while taking into account linear restrictions :))

Giving the most profitable optimal solution

the primary purpose of the simplex method in maximization is that it finds the best optimal solution by using iteration from one feasible solution to another in order to find the optimal solution.

To produce optimal solution that satisfy the given constraints.

To iteratively navigate the feasible region to find the optimal solution that maximizes the objective function

It finds the most profitable solution

 to improve the current solution and move towards the optimal solution.

To optimize and find the best solution

The Simplex method is an approach for determining the optimal value of a linear program by hand. 

 an optimal solution to satisfy the given constraints and produce a maximum zeta value.

The yield the best possible and accurate answer. Even if it's repetitive, the answer will come up in the end with a high precision.

To produce an optimal solution

The simplex method is an algorithm used to solve linear programming problems, both for maximizing and minimizing objectives, by finding the optimal solution at the vertex of the feasible region. In the context of maximizing problems with linear programming, the primary purpose of the simplex method is to determine the optimal combination of decision variables that maximizes the objective function while satisfying the given constraints.

produces an optimal solution to satisfy the given constraints and produce a maximum zeta value.