Module 3

Question 1

A method of dealing with decision problems that can be expressed as constrained linear models.

Answer 1

Linear programming

Question 2

result of Air Force research project concerned with computing the most efficient and economical way to distribute men, weapons and supply from different fronts during World War I

Answer 2

Linear Programming

Question 3

Who suggested renaming “programming in a linear structure” as “linear programming”

Answer 3

Tjalling Koopmans

Question 4

producing a plan or procedure that determines the solution to a problem

Answer 4

Programming

Question 5

a two-dimensional geometric analysis of LP problems with two decision variables

Answer 5

Graphical Solution Method

Question 6

American mathematical scientist who created linear programming

Answer 6

George Bernard Dantzig

Question 7

an expression, which shows the relationship between the variables in the problem and the firm’s goal

Answer 7

Objective Function

Question 8

(or explicit constraint) is a limit on the availability of resources.

Answer 8

Structural Constraint

Question 9

(or implicit constraint) it restricts all the variables to zero and positive solution

Answer 9

Non-negativity constraint

Question 10

the highest (for maximization problem) or lowest value (for minimization problem) of the objective function.

Answer 10

Optimal Value

Question 11

combination of decision variable amounts that yields the best possible value of the objective function and satisfies all the constraints.

Answer 11

Optimal solution

Question 12

the set of combinations of values for the decision variables that satisfy the non-negativity conditions and all the constraints simultaneously that is the allowable decisions

Answer 12

Feasible Region

Question 13

the corner of the feasible region

Answer 13

Extreme Point

Question 14

Special cases in Linear Programming (Graphical Method)

Answer 14

Multiple Optimal Solution
Infeasibility
Redundancy
Unbounded

Question 15

An LP model that has a multiple optimal solution or more than one optimal solution.

Answer 15

Multiple optimal solution

Question 16

A case where an LP model contains no feasible solution even though all constraints are being satisfied; that is, there no are points which satisfy all constraints.

Answer 16

Infeasibility

Question 17

A condition of an LP model wherein there is a constraint which does not affect the feasible region

Answer 17

Redundancy

Question 18

A condition of an LP model when the objective function of a linear programming problem can be made infinitely large without violating any of the constraints.

Answer 18

Unbounded

Question 19

An iterative technique that begins with a feasible solution that is not optimal, but serves as a starting point.

Answer 19

Simplex Method

Question 20

is a simplex method which consists of the sequence of steps (row operations) performed in moving one basic feasible solution to another.

Answer 20

Iteration

Question 21

the column in a simplex tableau indicating the quantities of the variables is in a solution

Answer 21

Right Hand Side (RHS)

Question 22

the variables included in a basic solution.

Answer 22

Basic Variables

Question 23

a table used to keep track of the calculations made when the simplex method is employed.

Answer 23

Simplex Tableau

Question 24

the column in any solution to a maximization problem which has the lowest negative value in the last row

Answer 24

Pivot Column

Question 25

the row in the simplex tableau corresponding to the basic variable that will leave the solution

Answer 25

Pivot Row

Question 26

elements common to both the pivot column and the rows representing variables in the solution

Answer 26

Intersectional Elements

Question 27

the element of the simplex tableau that is in both the pivot row and the pivot column.

Answer 27

Pivot

Question 28

Special cases in Linear Programming (Simplex Method)

Answer 28

Multiple Optimal Solution Infeasibility Unbounded Solution Degeneracy (Tie in pivot row) Tie for the optimum column

Question 29

It arises if there is a zero entry in the final tableau where the variable column is located, this indicates an alternative solution

Answer 29

Multiple Optimal Solution

Question 30

This is a condition resulting from a tie in the test ratios determining the replaced row, which produces a basic variable with a zero value. It may develop when a problem contains redundant constraints, that is, one or more of the constraints in the formulation make it unnecessary

Answer 30

Degeneracy

Question 31

This is a condition where the greatest positive or least negative entries in the last row have the same values; thus there is a tie in the pivot column. One of two tied columns should be selected arbitrarily. Although one choice may require fewer iterations than the other, there is also no way of knowing this beforehand.

Answer 31

Tie for the optimum column