1. Unbounded solution: When the feasible region of an LP problem has no upper bound, the solution is said to be unbounded. This happens when the objective function can keep increasing or decreasing indefinitely without reaching an optimal solution. Source: Management Science: The Art of Modeling with Spreadsheets by Stephen G. Powell and Kenneth R. Baker.
2. Infeasible solution: If the constraints of an LP problem are contradictory or infeasible, there is no feasible solution that satisfies all the constraints. This means that the problem cannot be solved within the given constraints. Source: Introduction to Operations Research by Frederick S. Hillier and Gerald J. Lieberman.
3. Degeneracy: Degeneracy occurs when multiple solutions exist for an LP problem, and the simplex method may get stuck at an intermediate solution. This can slow down the solution process and make it more difficult to find the optimal solution. Source: Operations Research: An Introduction by Hamdy A. Taha.
4. Multiple optimal solutions: Some LP problems may have multiple optimal solutions, where different combinations of decision variables lead to the same optimal objective function value. This can make it challenging to determine the best solution among the alternatives. Source: Introduction to Mathematical Programming: Operations Research, Volume 1 by Wayne L. Winston.
Outline the special cases (including sources) associated with solving an LP problem
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