In linear programming infeasible solutionsa)fall on the x = 0 planeb)f...
In linear programming infeasible solutions fall outside the feasible region .
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In linear programming infeasible solutionsa)fall on the x = 0 planeb)f...
Feasible Solutions in Linear Programming
In linear programming, feasible solutions refer to the set of values for decision variables that satisfy all constraints in the problem. These solutions lie within the feasible region, which is defined by the intersection of all constraints.
Infeasible Solutions
Infeasible solutions, on the other hand, are values of decision variables that do not satisfy one or more constraints in the linear programming problem. These solutions fall outside the feasible region and cannot be considered valid solutions to the problem.
Characteristics of Infeasible Solutions
- Infeasible solutions do not satisfy all constraints simultaneously.
- They fall outside the feasible region, making them impossible to achieve within the given constraints.
- Infeasible solutions can be identified by observing whether they violate any of the constraints in the linear programming problem.
Identifying Infeasible Solutions
- Infeasible solutions can be visualized graphically by plotting the constraints and observing where they intersect.
- If the intersection of constraints does not form a feasible region, any solutions falling outside this region are considered infeasible.
- Infeasible solutions can also be identified computationally by solving the linear programming problem and checking if any constraints are violated.
Conclusion
In linear programming, infeasible solutions fall outside the feasible region and do not satisfy all constraints in the problem. It is important to identify and eliminate these solutions to find the optimal feasible solution to the problem.