**COM315 Decision Support Systems**

**Module 1 Discussion **

What is the difference between a deterministic variable versus a probabilistic variable?

What makes one model deterministic and another model probabilistic? Give examples.

Identify and discuss the steps in the decision modeling process. Give examples.

How do we use the information about machine capacity in Part A of Sample Problem 1-29?

What would the revenues be for part A and B in Problem 1-29? How did you calculate them?

What would the profits be for each machine in part C in Problem 1-29? How did you calculate them?

**COM315 Decision Support Systems**

**Module 2 Discussion **

In reference to sample problem 2-23, explain how the constraint equation P – 5I <= 0 was derived from the statement, “It has been agreed that the number of print media ads will be no more than five times the number of Internet bursts.

In reference to sample problem 2-23, explain one of the Excel equations in column L.

In reference to the sample problem 2-23, go to the Data tab and select one of the Solver parameters and explain how Solver uses it in solving the problem.

What is an unbounded solution and under what conditions is it possible?

Explain the fact that a linear programming problem can have an infinite number of solutions.

What are the assumptions of a linear programming model?

Discuss an assumption of a linear programming model and how the assumption would be violated.

Identify four special situations that can be encountered in a linear programming problem.

Discuss one of the four special circumstances that can be encountered in a linear programming problem. Give an example.

**COM315 Decision Support Systems**

**Module 3 Discussion **

In reference to sample problem 3-5, explain one of the Excel equations in column E.

In reference to the sample problem 3-5, go to the Data tab and select one of the Solver parameters and explain how Solver uses it in solving the problem.

Chapter 3 examines several types of linear programming problems. Explain one of the problem types including the Solver set-up strategy for solving such a problem type. What are the typical the decision variables associated with the problem? What types of constrains are typically encountered in such a problem. Give examples.

**COM315 Decision Support Systems**

**Module 4 Discussion **

Explain how a change in resource availability can affect the optimal solution of a problem.

Explain how a change in an objective function coefficient can affect the optimal solution of a problem.

What is the 100% rule? What is its role in analyzing the impact of simultaneous changes in model input data values?

What is the pricing out procedure? How can a firm benefit from using the pricing out procedure?

What is a sensitivity report? How is it used?

How do we detect the presence of alternative optimal solutions from a Solver Sensitivity Report?

What is the shadow price? Give an example. Why would a firm find information regarding the shadow price of a resource useful?

Explain slack and surplus. Give an example of each.

Explain binding and non-binding constraints. How can you tell in the sensitivity report that a constraint is binding.

**COM315 Decision Support Systems**

**Module 5 Discussion **

Explain the difference between a balanced transportation model and an unbalanced transportation model. How does the fact that a model is balanced or unbalanced affect the constraints of the model?

Explain the difference in the approaches in solving balanced and unbalanced transportation problems.

What is the enumeration approach to solving assignment models? Is it a practical way to solve 5 row x 5 column models? Why?

What is the minimum-spanning tree model? What types of problems can be solved using this type of model?

What is the maximal-flow model? What types of problems can be solved using this type of model?

What is a shortest path model? What type of problem can be solved using this type of model?

What is a flow balance constraint? How is it implemented at each node in a network?

**COM315 Decision Support Systems**

**Module 6 Discussion **

Compare the similarities and differences of linear programming (LP) and goal programming (GP).

What is the difference between pure and mixed Integer Programming (IP) problems? Which do you think is most common, and why?

What is meant by satisficing, and why is the term often used in conjunction with Goal Programming?

What are deviation variables? How do they differ from decision variables in traditional LP problems?

If you were the president of the college and were employing GP to assist in decision- making, what might your goals be? What kinds of constraints would you include in your model?

What does it mean to rank goals in GP? How does this affect the problem’s solution?

Provide your own examples of problems where the objective is nonlinear and one or more constraints are nonlinear.

What are some of the questions that can be answered with project management?

What are the major differences between PERT and CPM?

What is an activity? What is an immediate predecessor?

Discuss what is meant by critical path analysis. What are critical path activities, and why are they

important?

What are the EST and the LST? How are they computed?

Describe the meaning of slack and discuss how it can be determined.

What is a relaxed problem or relaxed solution? Give an example.

What are deviational variables? Give an example.

Discuss some of the differences between Activity-on-Node (AON) and Activity-on-Arc (AOA) diagrams.

**COM315 Decision Support Systems**

**Module 7 Discussion **

Give an example of a good decision you made that resulted in a bad outcome. Also, give an

example of a bad decision you made that resulted in a good outcome. Why was each decision

good or bad?

What is an alternative? What is an outcome?

Discuss the differences between decision making under uncertainty and decision making under risk and explain what decision making strategies are used in each situation.

What is the EMV? Give an example.

What is the difference between the EVPI and the EV with PI?

Explain Opportunity Loss and give an example.

What is the purpose of Bayesian analysis? Describe how you would use Bayesian analysis in the decision-making process.

What is Utility Theory and how is it used?

What is a queuing problem? What are the components of a queuing system?

What are the assumptions underlying common queuing models?

Describe the important operating characteristics of a queuing system.

Describe three situations in which the FIFO discipline rule is not applicable in queuing analysis.

Explain what is meant by a finite or limited waiting line. Provide four examples.

Do you think the Poisson distribution is a good estimation of arrival rates in the following queuing

systems? Defend your position in each case.

a. School cafeteria

b. Barbershop

c. Dentist’s office

d. College class

e. Movie theater

What’s the difference between single-server and single-phase? Give an example of each.

What is Kendall notation? Give some examples.

Explain the costs associated with a queue. Explain the typical relationship between these costs.

**COM315 Decision Support Systems**

**Module 8 Discussion **

What is the difference between a casual model and a time-series model?

What is the meaning of least squares in a regression model?

What are some of the problems and drawbacks of the moving average forecasting model?

What effect does the value of the smoothing constant have on the weight given to the past forecast and the past observed value?

Why wouldn’t a company always store large quantities of inventory to eliminate shortages and

stock outs?

What are some of the assumption made in using the EOQ model?

What is the ROP? How is it determined?

What assumptions are made in the EPQ model?

What happens to the EPQ model when the daily production rate becomes very large?

Describe what is involved in solving a quantity discount problem.Discuss the methods used to determine safety stock when the stock out cost is known and when the stock out cost is unknown.