COB 291 STUDY GUIDE TEST PAPER
QUESTIONS WITH THOROUGH ANSWER
EXPLANATIONS
●● bi
Answer: RHS; Amount of resource required and/or available, depending
upon sign of inequality/if it is an equality constraint
●● Cj
Answer: Objective function coefficient; the change in Z value with
additional production of corresponding decision variable.
●● Non-negativity
Answer: one constraint every LP problem has.
●● Non-negativity and Sum of Decision Variables = 1
Answer: Constraints needed when an LP problem has decision variables
that represent proportions or percentages.
●● Key characteristics of Mixing/Blending Problems
Answer: When writing objective function/constraints, percentages
representing parameters are generally turned into decimals for purposes
, of the problem and coming up with an answer that actually makes sense.
Non-negativity and Sumer of Decision Variables = 1 constraints
●● 5 steps to formulating LP models
Answer: - *Understand* the problem.
- Identify the *Decision Variables*
- State the *objective function* as a *linear combination* of *decision
variables*
- State the *constraints* as *linear combinations* of *decision
variables*
- Identify and *upper or lower boundaries* on the decision variables
●● Decision variables
Answer: what you as the decision maker has control over
●● Optimal/Z-value and basic variable
Answer: the components that have to be included in the *basis*
●● What should never be on the RHS and must be "simplified"
Answer: decision variables
●● Basic vs Non-basic variables
Answer: - A *basic* variable is a non-zero variable.
QUESTIONS WITH THOROUGH ANSWER
EXPLANATIONS
●● bi
Answer: RHS; Amount of resource required and/or available, depending
upon sign of inequality/if it is an equality constraint
●● Cj
Answer: Objective function coefficient; the change in Z value with
additional production of corresponding decision variable.
●● Non-negativity
Answer: one constraint every LP problem has.
●● Non-negativity and Sum of Decision Variables = 1
Answer: Constraints needed when an LP problem has decision variables
that represent proportions or percentages.
●● Key characteristics of Mixing/Blending Problems
Answer: When writing objective function/constraints, percentages
representing parameters are generally turned into decimals for purposes
, of the problem and coming up with an answer that actually makes sense.
Non-negativity and Sumer of Decision Variables = 1 constraints
●● 5 steps to formulating LP models
Answer: - *Understand* the problem.
- Identify the *Decision Variables*
- State the *objective function* as a *linear combination* of *decision
variables*
- State the *constraints* as *linear combinations* of *decision
variables*
- Identify and *upper or lower boundaries* on the decision variables
●● Decision variables
Answer: what you as the decision maker has control over
●● Optimal/Z-value and basic variable
Answer: the components that have to be included in the *basis*
●● What should never be on the RHS and must be "simplified"
Answer: decision variables
●● Basic vs Non-basic variables
Answer: - A *basic* variable is a non-zero variable.