ZZCA6510 Decision Making in Analytics

Preface
This assignment has two components. The first component is designed to demonstrate your knowledge of the basic prescriptive
decision-making tools and techniques. In this part, you are required to formulate and/or solve several simple decision problems us
Decision Making Analytics (DMA)/ approaches learnt in this course during weeks 4-6. The second component is designed to
demonstrate your critical thinking and advanced learning to tackle real-world scenarios (that is non-textbook type problems).
What you need
Preparation
To be able to complete the first component of this assignment, you need to read /review the chapters /topics scheduled from week
week 6, from the recommended textbook, and lecture notes /slides. For the second component, consider all the topics covered in
course during those weeks, but use your critical thinking and advanced learning.
Formulation skill: learning formulation is an important goal in this course (including notations) as the big and complex problems
cannot be dealt with Excel Solver alone.
Assumption: do not make any assumption for Component-A of the assignment.
Instructions
Purpose
This assignment will ensure the understanding of the fundamental concepts of prescriptive analytics, such as linear programming
integer programming, transportation problems, network optimisation models, and goal programming. This assignment will further
ensure the understanding of the fundamental concepts of linear programming such as decision variable, objective function, constr
feasibility, model formulation, feasible region and the various types of solutions. Moreover, you are expected to visually understan
effect on the feasible region under different conditions and the relationship of the various parameters in the model. You will also
understand how to build a spreadsheet model of a given linear programming problem and interpret solver solutions. This assignm
will also strengthen the understanding of sensitivity analysis in linear programming and the basic concepts of network modelling. Y
should be able to interpret the solutions in real life by analysing the report generated. The extended question (Task 3) requires cri
thinking and independent study /literature search. This question is designed to help develop the skills needed to solve different an
complex practical problems.
Component A: Demonstrating Basic Knowledge in DMA
Task 1: Linear Programming 1
SMRM Computer manufacture produces several lines of decorative and functional laptop items. The most recent order was for 12
office laptops for a government agency. The sales and production departments must work together to determine delivery schedule
Each laptop consists of three major components assembled within the SMRM factory precinct: the body of the laptop, the keyboa
component and the circuit board. Although the processes used in assembling those three components vary, there are three areas
where the production manager is concerned about the availability of resources. These three areas, their usage by the three
components, and their availability are detailed in the table below.
Resource Body of the laptop Keyboard component Circuit board Available
Metal alloy 12 5 1 15,000 units
Machining 18 20 10 36,000 minutes
Finishing 15 5 1 12,000 minutes
A quick look at the amounts available confirms that SMRM does not have the resources to fill this contract. A subcontractor, who c
assemble an unlimited number of each of the three components, quotes the prices below.
Body of the laptop 1000 600
Keyboard component 900 400
Circuit Board 1000 500
Now,
a) Formulate a linear programming model (showing the decision variables, objective function and constraints) that can be used to
determine how to fill the order (i.e., by determining how many to assemble inhouse and how many to subcontract for each compo
for 1200 office laptops at the minimum cost.
b) Solve the LP model by Excel Solver and provide us with the optimal values for each decision variable. You must submit your so
spreadsheet file along with the assignment report.
Task 2: Assignment Problem
James Haller has been appointed as a rostering manager to employ staff for the SMRM Computer manufacturer’s production floo
Therefore, James needs to develop a weekly schedule so that he knows how many staff need to be on roster each day so that he
offer jobs. He has been asked to minimise the staff salary bill for the production floor while scheduling employees. The production
operates seven days a week with varying numbers of products leading to a variable demand each day for staff. Considering the
staffing at the other production floors, James estimates the number of staff required to support the production floor’s operations as
follows:
DAYS OF THE WEEK STAFF REQUIRED
Sunday 12
Monday 18
Tuesday 14
Wednesday 17
Thursday 20
Friday 16
Saturday 19
As the staff are entitled to have two consecutive days off each week, the possible shifts and salaries for the staff are as follows:
SHIFT DAYS OFF WEEKLY SALARY
1 Sunday and Monday $850
2 Monday and Tuesday $900
3 Tuesday and Wednesday $900
4 Wednesday and Thursday $900
5 Thursday and Friday $900
6 Friday and Saturday $850
7 Saturday and Sunday $800
James Haller needs to know how many staff there are on each shift and what the salary bill is.
Now,
a) Formulate a linear programming model (showing the decision variables, objective function and constraints) that can be used
determine how many staff should be on each shift and what the salary bill will be.
b) Solve the LP model by Excel Solver and provide us with the optimal values for each decision variable. You must submit your
Component B: Demonstrating Critical Thinking and Learning in DMA (Based on individual
independent study and research)
All topics covered in Weeks 4-6 will support you with this assessment.
Task 3: Problem for the project
Instructions
In this task, you need to write a report describing a decision problem that you believe could be addressed by using a Prescriptive
Analytics Technique (demonstrated between weeks 4-6) to improve the situation. A few guidelines can be-
Explain how you identified the problem and justify why you think you have identified it correctly.
Describe the background of the problem and the reason for its selection.
Describe the limitations and assumptions that may need to be considered.
You may also discuss the current practice and the existing difficulties.
You are advised to give the reasons for the chosen Prescriptive Analytics tool/technique, the advantages & disadvantages,
resources required, and the computational time required.
Analyse the results and provide sensitivity analysis, if any.
Describe your computational difficulties and experiences. You may also mention the things you wanted to do but could not do d
time or other constraints.
Ensure that the topic and/or associated material is not/cannot be security classified.
You are encouraged to add anything that you find relevant to the assignment. Notably, you need to solve your problem by using o
one Prescriptive Analytic tool/technique (e.g., Linear Programming, Integer Programming, Goal Programming, Transportation and
Assignment Problems, Network Optimisations).
A Few Decision Making Problems related to Prescriptive Analytic Technique
A few decision making problems which can be dealt with prescriptive analytic techniques are:
Optimising the production quantity for multiple items under varied company-wide constraints;
finding the optimal amount of purchase quantities for multiple items under capital and capacity constraints;
scheduling or rostering employees in a restaurant;
finding the shortest path to transport a medical emergency product;
determining the optimal path for transporting medical samples;
finding the transportation network for an ambulance connecting multiple hospitals;
conveying perishable items across multiple fresh food markets;
buying a car without any rigid budget;
assigning nurses for medical patience in a local hospital; and
minimising inventory in a typical supply chain setting.
Notably, this list is non-exhaustive and you must select your problem based on your professional experience, real-life contexts, or literature
search.


Quiz Question 2

Uber Canberra has identified 10 primary pickup and drop locations for taxi riders in Canberra city. In an effort to minimise travel time
and improve customer service and the utilisation of the company's fleet of taxis, management would like the taxi drivers to take the
shortest route between locations whenever possible. Using the following network of roads and streets, what path should a driver
beginning at location 1 take to reach location 10? The travel times in minutes are shown on the arcs of the network. Note that there are
two one-way streets and that the arrows indicate the direction.
a) Formulate a linear programming model (showing the decision variables, objective function and constraints) that can be used to
determine the shortest route between locations 1 to 10.
b) Solve the LP model by Excel Solver using the following network of roads and streets, and determine what path should a driver take
to begin at location 1 to reach location 10?
c) What will be the shortest travel time for the selected path?
Enter your answer in the text field below. You will submit the spreadsheet you used to solve the problem at the end of this quiz.