UTK Math 123 Final Exam| Questions and Answers | 2026/2027 Update | 100%
correct| graded a+!!!! | pass!!
True _answer-In the final tableau of a simplex method problem, if the problem has a
solution, the last column will contain no negative numbers above the bottom row.
False _answer-In a feasible basic solution all the variables (with the possible exception
of the objective) are positive.
True _answer-If a linear programming problem has a solution at all, it will have a
solution at some corner point of the feasible region.
True _answer-The feasible region of a linear programming problem with two unknowns
may be bounded or unbounded.
False _answer-The solution set of 2x - 3y < 0 is below the line 2x - 3y = 0.
True _answer-Every minimization problem can be converted into a maximization
problem.
True _answer-The simplex method can be used to solve all linear programming
problems that have solutions.
False _answer-Every minimization linear programming problem can be converted into a
standard maximization linear programming problem.
True _answer-If, at any stage of an iteration of the simplex method, it is not possible to
compute the ratios (division by zero) or the ratios are all negative, then the standard
linear programming problem has no solution.
False _answer-The graph of a linear inequality consists of a line and some points on
both sides of the line.
, True _answer-The following linear programming problem has an unbounded feasible
region:
True _answer-The following is a standard maximum linear programming problem:
True _answer-Some linear programming problems have more than one solution.
False _answer-A linear programming problem with an unbounded feasible region never
has a solution.
True _answer-In a standard maximization linear programming problem, each constraint
inequality may be written so that it is less than or equal to a nonnegative number.
False _answer-The following is a standard maximum linear programming problem:
A non-unit column has a zero below the horizontal line _answer-When is a linear
programming problem considered infinitely many solutions?
The test ratios are all negative _answer-When is a linear programming problem
considered no solution (unbounded)?
There is a negative constant but no negative number to pick in that row _answer-When
is a linear programming problem considered no solution (no feasible region/empty)?
False _answer-There can only be one saddle point in a payoff matrix.
True _answer-If a game has expected value 2, then the row player will gain an average
of two points per play assuming both players use their optimal mixed strategies.
False _answer-The payoff matrix is always a square matrix.
False _answer-A negative payoff indicates a loss to the column player.
False _answer-Some strictly determined games do not have saddle points.
True _answer-Your best response is a pure strategy if the game is strictly determined.
False _answer-According to the principles of game theory, your opponent can always
anticipate your move.
True _answer-Different saddle points in the same payoff matrix always have the same
payoff.
True _answer-If the value of a strictly determined game is positive, it favors the row
player.
correct| graded a+!!!! | pass!!
True _answer-In the final tableau of a simplex method problem, if the problem has a
solution, the last column will contain no negative numbers above the bottom row.
False _answer-In a feasible basic solution all the variables (with the possible exception
of the objective) are positive.
True _answer-If a linear programming problem has a solution at all, it will have a
solution at some corner point of the feasible region.
True _answer-The feasible region of a linear programming problem with two unknowns
may be bounded or unbounded.
False _answer-The solution set of 2x - 3y < 0 is below the line 2x - 3y = 0.
True _answer-Every minimization problem can be converted into a maximization
problem.
True _answer-The simplex method can be used to solve all linear programming
problems that have solutions.
False _answer-Every minimization linear programming problem can be converted into a
standard maximization linear programming problem.
True _answer-If, at any stage of an iteration of the simplex method, it is not possible to
compute the ratios (division by zero) or the ratios are all negative, then the standard
linear programming problem has no solution.
False _answer-The graph of a linear inequality consists of a line and some points on
both sides of the line.
, True _answer-The following linear programming problem has an unbounded feasible
region:
True _answer-The following is a standard maximum linear programming problem:
True _answer-Some linear programming problems have more than one solution.
False _answer-A linear programming problem with an unbounded feasible region never
has a solution.
True _answer-In a standard maximization linear programming problem, each constraint
inequality may be written so that it is less than or equal to a nonnegative number.
False _answer-The following is a standard maximum linear programming problem:
A non-unit column has a zero below the horizontal line _answer-When is a linear
programming problem considered infinitely many solutions?
The test ratios are all negative _answer-When is a linear programming problem
considered no solution (unbounded)?
There is a negative constant but no negative number to pick in that row _answer-When
is a linear programming problem considered no solution (no feasible region/empty)?
False _answer-There can only be one saddle point in a payoff matrix.
True _answer-If a game has expected value 2, then the row player will gain an average
of two points per play assuming both players use their optimal mixed strategies.
False _answer-The payoff matrix is always a square matrix.
False _answer-A negative payoff indicates a loss to the column player.
False _answer-Some strictly determined games do not have saddle points.
True _answer-Your best response is a pure strategy if the game is strictly determined.
False _answer-According to the principles of game theory, your opponent can always
anticipate your move.
True _answer-Different saddle points in the same payoff matrix always have the same
payoff.
True _answer-If the value of a strictly determined game is positive, it favors the row
player.
