deck_17801041 Flashcards
Use for problems involving the
allocation of resources to obtain
optimal effectiveness.
Allocation Model
Mathematical programming is **the
broad term for tools that are used to
solve problems **in which the
decision-makers must allocate
limited resources among various
activities to optimize a managerial
objective. These tools include linear
programming and distribution model
Allocation Model
refers to the property of having a
random probability distribution that
can be statistically analyzed but may
not be predicted accurately.
Stochastic Method (Probabilistic Model)
are costs such as** rent, salaries,
advertising, and other overhead
costs** that remain the same no
matter how much of the product is
manufactured or sold.
Fixed Cost
The s**implex method **which was
developed by **George B. Dantzig **
together with US Department of the
Airforce, is an iterative technique for
solving more unknown variables that
are geometrically difficult to plot in
the graph.
Albert Dantzig
The consequences of
each alternative course of action can
be found at the intersection of a
given alternative and the
corresponding state of nature.
Payoffs
presented at the top of the table are
the possible “—– – —–” or
called **events. **
State of Nature
the problem as s1 s2 s3. —- — —- can also be presented as
rows.
State of Nature
are given in
percentage and are usually placed
at the top of the table. The
assumption is that only one of the
given states of nature will happen n
the future. The sum of the
probabilities must be equal to 1.
Probabilities
The most common approach to
solve decision-making—— is
the expected payoff criterion.
Decision Under Risk
The decision-maker must select the
alternative with the —– ——
payoff.
The decision-maker must select the
alternative with the **highest expected **
payoff.
The decision maker —- —-
situation, also called **“deterministic”
situation. **
Under Certainty
The decision-maker** know with
certainty the consequence **of every
alternative or decision choice.
Under Certainty
It is a perfect** predictor of the future **
because of the availability of
complete information, naturally they
will choose the alternative that has
the best result.
Under certainty
the** decision-maker in this
situation can not estimate or does
not have knowledge** of the
probability of occurrence of possible
states of nature.
Under Uncertainty
However, the situation should not be
considered “——” since
the states of nature are known.
Total ignorance
Also called **Probabilistic or
Stochastic decision situations. **
Under Risk
is presented
with several options with a
corresponding probability of
occurrence.
Under Risk
- In this criterion, the decision-maker assumes that all states of nature
have equal probabilities to occur. - Then the highest expected payoff is
selected. - To compute for the expected payoffs,
the probabilities of 1 3 will be applied
to each of the 3 states of nature.
Laplace (Equal Likelihood)
- most suitable
for decision-makers who are neither
completely pessimistic nor
optimistic. - To select the best alternative, the
decision-maker will be using the
degree of optimism called “alpha, a” which is measured on a 0 to 1 scale
(where 0 = completely pessimistic
and 1 = completely optimistic). - The best alternative is the one with the highest weighted value (WV) for
maximization problems. - The main difficulty of using this
criterion is the measurement of
alpha
Hurwicz (The Criterion of Realism)
- is based on the concept of
Opportunity Lost, which
means an opportunity loss is
incurred whenever the
decision overlooks the best
alternative. - Choosing the alternative with
the minimum of all maximum
regrets. - Regret = Opportunity Lost – Payoff Received
o This is done without the
probabilities.
Regret
**requirements or restrictions placed **
on the firm by the operating
environment, stated in linear
relationships of the decision
variables.
Constraints
A variable added to the LHS of “Less
than or equal to” constraint to
convert it into an equality.
Slack Variables
A** table which is used to keep track
of the calculations **made at each
iteration when the simplex method is
employed.
Simplex Tableau
The **row corresponding to variable **
that will leave the table in order to
make room for another variable. It
contains the lowest quotient.
Pivotal Row
**Element at the intersection **of pivotal
row and pivotal column.
Pivot
Any basic feasible solution which
optimizes (maximizes or minimizes)
the objective function.
Optimal Solution
is appropriate for small problems
dealing with 2 decision variables and
with few constraints.
Graphical Method
