A feasible solution satisfies all constraints of a linear programming model including non-negativity restrictions, while an optimal solution is a feasible solution that achieves the highest or lowest possible objective function value.

A feasible solution satisfies all the constraints of a Linear Programming problem, while an optimal solution is the feasible solution that gives the best value of the objective function (maximum or minimum).

Example: A feasible solution follows all resource limits, while the optimal solution gives the highest profit or lowest cost among all feasible solutions.

A feasible solution is any solution that satisfies all the constraints and requirements of a linear programming problem, while an optimal solution is the feasible solution that gives the best possible value for the objective function, such as the maximum profit or minimum cost. In simple terms, every optimal solution is feasible, but not every feasible solution is optimal.