Reference no: EM133193008

BUS 4024 Business Decision-Making Through Advanced Analytics - George Brown College

Assignment Objective:
In this assignment, you will be implementing a range of management sciences analytical techniques to solve problems related to; decision analysis, waiting time and queueing, computer based simulation, and inventory management.

In this assignment you will be producing a written report FOR EACH case study, containing the following deliverables:

Component 1: Executive Summary of Solution Approach and Recommendations

• For each solution implementation provide a brief summary of; Presenting Problem, Solution Approach (include assumptions and sensitivities), Recommendations.
• Your audience is a business sponsor (not a management scientist) and information should be summarized in that context (2 to 3 paragraphs max)
• Ensure that all responses to case study questions are addressed (and clearly labelled) and integrated into your executive summary.
• In the APPENDIX of each Case Report please include the following:
1. The mathematically modelled solution(s) must be written (where applicable using an equation editor, not hand written with; variable names clearly defined (i.e. NOT X1, X2, ... etc.)
2. Where applicable, include clearly labelled and commented copies of all output solution and sensitivity reports for each executed solution scenario in your case
• Submit the completed report as XX_Case_Name_Report.doc file. (where XX is the enrolled group number (or First and Last Initials if a non-group assignment), followed by the Case Name)
• Solutions must be executable (in .xls)

Component 2: Executable Solution Implementation and Program Solution and Supplementary or Supporting Output

• Submit your executable implementation as a separate additional file named XX_Case_Name_Implementation. (where XX is the enrolled group number (or First and Last Initials if a non-group assignment), followed by the Case Name)
• Solutions must be executable (in .xls formats)

Instructions:

Case 1: Orca Carbon Capture

Perform a decision tree analysis of this problem for Orca and indicate the recommended solution. Is this the decision you believe the company should make? Explain your rationale.

Case 2: GBC Emergency Preparedness
A. First, consider a single-server waiting line model in which the available emergency vehicles are considered to be the server. Assume that victims arrive at the staging area ready to be transported to a hospital on average every 7 minutes and that emergency vehicles are plentiful and available to pick up and transport victims every 4.5 minutes. Compute the average waiting time for victims. Next assume that the distribution of service times is undefined, with a mean of
4.5 minutes and a standard deviation of 5 minutes. Compute the average waiting time for the victims.
B. Next consider a multiple-server model in which there are eight emergency vehicles available for transporting victims to the hospitals, and the mean time required for a vehicle to pick up and transport a victim to a hospital is 20 minutes. (Assume the same arrival rate as in Part !.) Compute the average waiting line, the average waiting time for a victim, and the average time in the system for a victim (waiting and being transported)
C. For the multiple-server model in Part B., now assume that there are a finite number of victims,
18. Determine the average waiting line, the average waiting time, and the average time in the system.
D. From the two hospitals' perspectives, consider a multiple-server model in which the two hospitals are servers. The emergency vehicles at the disaster scene constitute a single waiting line, and each driver calls ahead to see which hospital is most likely to admit the victim first, and travels to that hospital. Vehicles arrive at a hospital every 8.5 minutes, no average, and the average service time for the emergency staff to admit and treat a victim is 12 minutes. Determine the average waiting line for victims, the average waiting time, and the average time in the system.
E. Next, consider a single hospital, S. Michael's, which in an emergency disaster situation has 5 physicians with supporting staff available. Victims arrive at the hospital on average every 8.5 minutes. It takes an emergency room team, on average, 21 minutes to treat a victim. Determine the average waiting line, the average waiting time, and the average time in the system.

F. For the multiple-server model in Part E., now assume that there are a finite number of victims,
23. Determine the average waiting line, the average waiting time, and the average time in the system.
G. Which of these waiting line models do you think would be the most useful in analyzing a disaster situation? How do you think some, or all , of the models might be used together to analyze a disaster situation? What other types of waiting line models do you think might be useful in analyzing a disaster situation?

Case 3: Staples
Suppose the bank offers Kayla a commission discount (from 2.25% to 2.0%) on any loan amount eval to or greater that $500,000. What would Staple's optimal loan amount be?

Attachment:- Business Decision-Making Through Advanced Analytics.rar