Ch 9 questions word

Section 9.2 Review Questions (Major modeling issues)
1. List and describe the major issues in modeling.
-problem identification and environmental analysis: scanning the
environment to figure out what problems exist and can be solved via a
model
-variable identification: identifying the critical factors in a model and their
relationships
-forecasting: predicting the future
-model categories: selecting the right type of model for the problem or subproblem
-model management: coordinating a firm’s models and their use
2. What are the major types of models used in DSS?
-Optimization with few alternatives
-Optimization via an algorithm
-Optimization via an analytical formula
-Simulation
-Heuristics (―rules of thumb‖)
-Predictive models
-Other models
Section 9.3 Review Questions (STRUCTURE OF MATHEMATICAL
MODELS FOR DECISION SUPPORT)
1. What is a decision variable?
A decision variable is a data element controlled by the decision maker, whose
possible values describe alternative courses of action.
2. List and briefly discuss the three major components of linear
programming.
Of the four components of any decision support mathematical model, linear
programming uses result (outcome) variables, decision variables, and
uncontrollable variables (parameters). Linear programming models do not use
the fourth component, intermediate result variables.
9.4 Review Questions (CERTAINTY, UNCERTAINTY, AND RISK)
1. Define what it means to perform decision making under assumed
certainty, risk,
and uncertainty. Slide 11*
-Decision making under assumed certainty: the values of all variables affecting
the decision, including future values, are known or can be assumed to be known.
-Decision making under risk: the exact value of decision variables is not known,
but their statistical probability distributions are known (or can be assumed to be).
-Decision making under uncertainty: even these distributions are not known.
Section 9.5 Review
SPREADSHEETS)
Questions
(DECISION
MODELING
WITH
1. Explain why a spreadsheet is so conducive to the development of DSS.
Because it provides an easily understood metaphor for the computation and
typically incorporates many powerful modeling functions.
Section 9.6 Review Questions (MATHEMATICAL PROGRAMMING
OPTIMIZATION)
1. Define the product-mix problem.
The product-mix problem is a linear programming problem in which a variety of
different products are made from common resources. Each product requires a
known resource mix and has a known profitability. Some resources are limited.
Total profitability is to be maximized.
A product-mix problem can be viewed as an allocation problem. The difference
is that a person formulating the problem as a product-mix problem is typically
interested in the quantities of each product to be produced, while a person
formulating the same problem as an allocation problem is usually interested in
the quantities of each resource to be used. The solutions are identical, and each
approach can produce both answers.
Section 9.7 Review Questions (MULTIPLE GOALS, SENSITIVITY
ANALYSIS, WHAT-IF ANALYSIS, AND GOAL SEEKING(
1. List some difficulties that may arise when analyzing multiple goals.
-It is usually difficult to obtain an explicit statement of the organization’s goals.
-The importance of specific goals may change over time or in different situations.
-Goals and subgoals are viewed and weighted differently by different people and
in different parts of the organization.
-Goals change in response to changes in the organization and its environment.
-The relationship between alternatives and their role in determining goals may be
difficult to quantify.
-Participants assess the importance (priorities) of the various goals differently.
2. List the reasons for performing sensitivity analysis.
Sensitivity analysis attempts to assess the impact of a change in input data or
parameters on the result variable(s). Reasons for using it listed in this section
include:
-Revising models to eliminate too-large sensitivities
-Adding details about sensitive variables or scenarios
-Obtaining better estimates of sensitive external variables
-Altering a real-world system to reduce actual sensitivities
-Accepting and using the sensitive (and hence vulnerable) real world,
leading to the continuous and close monitoring of actual results
3. Explain why a manager might perform what-if analysis.
A manager might perform what-if analysis to find out what will happen if a
particular action is taken. A manager might also perform what-if analysis to try
out several alternatives, choosing the one that works out best.
4. Explain why a manager might use goal seeking.
A manager might use goal seeking to find values of decision variables that enable
him or her to meet a predetermined criterion. For example, a manager may need
to find an advertising budget that will reach X households at a cost of not over
$Y.
Section 9.8 Review Questions (DECISION ANALYSIS WITH DECISION
TABLES AND DECISION TREES)
1. What is a decision table?
A decision table is a way to organize information in a systematic way to prepare
it for analysis.
2. What is a decision tree?
A decision tree is an alternative representation of a decision situation, in which
choices and states of nature are shown as alternating nodes along the branches of
a tree.
3. How can a decision tree be used in decision making?
By showing the decision maker the possible outcomes that could result from a
given choice, the tree gives the decision maker information by which to compare
choices.
4. Describe what it means to have multiple goals.
Having multiple goals means that a decision maker hopes to obtain the best
possible combination of several factors, all of which depend on the decision to
be made. For example, a student may want to find an instructor who is
entertaining, has a good reputation for teaching, grades easily, assigns little
homework, and whose section meets at convenient times.
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