EVPI (Expected Value of Perfect Information)
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=EVwPI - Max EMV at each value of P (vertical distance)
-the amount by which perfect information would increase our expected
payoff
-amount willing to pay for perfect information
- willing to pay more money for information in the middle bc it is more
uncertain
-the amount gained if the decision maker would have perfect information
objective function
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, the equation you are trying to optimize (max./min.) in a model
Multi variable system
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- systems with more than two variables; more complex
- ask the same four questions
operational decisions
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decisions that take a limited amount of time but have low consequence for
an incorrect decision (ex. assigning employees to jobs, purchasing lunch)
general vs. specific statement
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- general: good for any order quantity; in ratios; decision variable vales are
greater than or less than a number
- specific: only works at certain values; much stricter solution; decision
variable values are equal to a number and plugged into constraint as that
number
, good decisions
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-based on logic, considers ALL possible alternatives, examines ALL
available information about the future, more consistent
-good decisions sometimes result in UNFAVORABLE OUTCOMES because
the future is unpredictable
bad decisions
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-does not consider alternatives, does not consider all available information
-bad decisions can sometimes yield FAVORABLE results (luck)
- it's worse to make a bad decision with a favorable outcome than a good
decision with an unfavorable outcome
contribution margin
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= selling price - variable costs
- amount left over to cover fixed costs and go towards profit
-at breakeven point, contribution margin will only need to cover fixed costs
Optimal solution
Give this one a try later!
=EVwPI - Max EMV at each value of P (vertical distance)
-the amount by which perfect information would increase our expected
payoff
-amount willing to pay for perfect information
- willing to pay more money for information in the middle bc it is more
uncertain
-the amount gained if the decision maker would have perfect information
objective function
Give this one a try later!
, the equation you are trying to optimize (max./min.) in a model
Multi variable system
Give this one a try later!
- systems with more than two variables; more complex
- ask the same four questions
operational decisions
Give this one a try later!
decisions that take a limited amount of time but have low consequence for
an incorrect decision (ex. assigning employees to jobs, purchasing lunch)
general vs. specific statement
Give this one a try later!
- general: good for any order quantity; in ratios; decision variable vales are
greater than or less than a number
- specific: only works at certain values; much stricter solution; decision
variable values are equal to a number and plugged into constraint as that
number
, good decisions
Give this one a try later!
-based on logic, considers ALL possible alternatives, examines ALL
available information about the future, more consistent
-good decisions sometimes result in UNFAVORABLE OUTCOMES because
the future is unpredictable
bad decisions
Give this one a try later!
-does not consider alternatives, does not consider all available information
-bad decisions can sometimes yield FAVORABLE results (luck)
- it's worse to make a bad decision with a favorable outcome than a good
decision with an unfavorable outcome
contribution margin
Give this one a try later!
= selling price - variable costs
- amount left over to cover fixed costs and go towards profit
-at breakeven point, contribution margin will only need to cover fixed costs
Optimal solution
