Is it possible to have no optimal solution?
If the linear program does not have a feasible solution satisfying all constraints, then it can not have an optimal solution. In other words, if the value of the objective function can be increased without bound in a linear program with an unbounded feasible region, there is no optimal maximum solution.
How do you find the optimal solution?
An optimal solution is a feasible solution where the objective function reaches its maximum (or minimum) value – for example, the most profit or the least cost. A globally optimal solution is one where there are no other feasible solutions with better objective function values.
What is no optimal solution?
A linear program is infeasible if there exists no solution that satisfies all of the constraints — in other words, if no feasible solution can be constructed. It may stem from an error in specifying some of the constraints in your model, or from some wrong numbers in your data.
What if Solver Cannot find a feasible solution?
If you are using the Evolutionary Solving method, the evolutionary algorithm was unable to find a feasible solution; it might succeed in finding one if you run it with different initial values for the variables and/or increase the Precision value in the Solver Options dialog (which reduces the infeasibility penalty.
What is the difference between feasible region feasible solution and optimal solution?
A feasible solution satisfies all the problem’s constraints. An optimal solution is a feasible solution that results in the largest possible objective function value when maximizing (or smallest when minimizing).
What is degenerate basic feasible solution?
Degenerate basic feasible solution: A basic feasible solution where one or more of the basic variables is zero. Discrete Variable: A decision variable that can only take integer values. Feasible Solution: A solution that satisfies all the constraints. Feasible Region: The set of all feasible solutions, i.e., S. 1.
Is every optimal solution is feasible solution?
The values of the decision variables must satisfy a set of constraints, each of which must be a linear inequality or linear equality. Definition: An optimal solution to a linear program is the feasible solution with the largest objective function value (for a maximization problem).
What is a feasible solution and optimal solution?
A feasible solution satisfies all the problem’s constraints. An optimal solution is a feasible solution that results in the largest possible objective function value when maximizing (or smallest when minimizing). A graphical solution method can be used to solve a linear program with two variables.