![]() ![]() In some cases, the target function has one optimal value for several combinations of variable values, hence the problem has non-uniqueness of the optimum. An optimal solution is such admissible values of variables, at which the target function is extreme, i.e. An admissible solution is non-negative values of variables for which the constraints are satisfied, and an admissible domain is a set of admissible solutions. ![]() When solving problems in linear programming, the following basic concepts are used. If a feasible region is empty (contains no points), then the constraints are inconsistent and the problem has no solution. If the feasible region can be enclosed in a sufficiently large circle, it is called bounded otherwise it is called unbounded. ![]() What is bounded and unbounded in linear programming? For example, if a linear program is a min- imization problem and unbounded, then its objective value can be made arbitrarily small while maintaining feasibility. What does it mean for a linear program to be unbounded?Ī linear program is unbounded if it is feasible but its objective function can be made arbitrarily “good”.
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