MSIS 3223 CHAPTER 2 EXAM QUESTIONS WITH
CORRECT ANSWERS LATEST UPDATE
problem formulating
process of translating the verbal statement of a problem into a mathematical statement;
an art that can only be mastered with practice and experience; also known as modeling
non-negativity constraints
general feature of all linear programming problems and may be written in the
abbreviated form S, D >= 0
linear functions
mathematical functions in which each variable appears in a separate term and is raised
to the first power
proportionality
1 of the 3 assumptions necessary for linear programming model to be appropriate;
means that the contribution to the objective function and the amount of resources used
in each constraint are proportional to the value of each decision variable
additivity
1 of the 3 assumptions necessary for linear programming model to be appropriate;
means that the value of the objective function and the total resources used can be
found by summing the objective function contribution and the resources used for all
decision variables
divisibility
1 of the 3 assumptions necessary for linear programming model to be appropriate;
means that the decision variables are continuous - this assumption plus the non-
negativity constraint mean that decision variables can take on any value greater than or
equal to zero
Linear programming models
special type of mathematical programming model that is to be maximized or minimized
in that the objective function and all constraint functions are linear and vars that are all
restricted to non-neg values; mathematical model with a linear objective function, a set
of linear constraints, and non negative vars
Slack variables
added to the LHS of the formulation of a linear programming problem to represent the
slack/idle capacity; represents unused capacity so have coefficients of zero in the
objective function; value of this var can be interpreted as an amount of unused resource
standard form
when a linear program is written in a form with all constraints expressed as equalities;
objective function coefficients for slack variables are zero; the optimal solution of the
form of a linear program is the same as the optimal solution of the original formulation of
the linear program
redundant constraints
Can be removed from a linear programming model without affecting the optimal solution
- do not affect the feasible region
CORRECT ANSWERS LATEST UPDATE
problem formulating
process of translating the verbal statement of a problem into a mathematical statement;
an art that can only be mastered with practice and experience; also known as modeling
non-negativity constraints
general feature of all linear programming problems and may be written in the
abbreviated form S, D >= 0
linear functions
mathematical functions in which each variable appears in a separate term and is raised
to the first power
proportionality
1 of the 3 assumptions necessary for linear programming model to be appropriate;
means that the contribution to the objective function and the amount of resources used
in each constraint are proportional to the value of each decision variable
additivity
1 of the 3 assumptions necessary for linear programming model to be appropriate;
means that the value of the objective function and the total resources used can be
found by summing the objective function contribution and the resources used for all
decision variables
divisibility
1 of the 3 assumptions necessary for linear programming model to be appropriate;
means that the decision variables are continuous - this assumption plus the non-
negativity constraint mean that decision variables can take on any value greater than or
equal to zero
Linear programming models
special type of mathematical programming model that is to be maximized or minimized
in that the objective function and all constraint functions are linear and vars that are all
restricted to non-neg values; mathematical model with a linear objective function, a set
of linear constraints, and non negative vars
Slack variables
added to the LHS of the formulation of a linear programming problem to represent the
slack/idle capacity; represents unused capacity so have coefficients of zero in the
objective function; value of this var can be interpreted as an amount of unused resource
standard form
when a linear program is written in a form with all constraints expressed as equalities;
objective function coefficients for slack variables are zero; the optimal solution of the
form of a linear program is the same as the optimal solution of the original formulation of
the linear program
redundant constraints
Can be removed from a linear programming model without affecting the optimal solution
- do not affect the feasible region
