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Assessment Details and Submission Guidelines
BusinessAnalyticsand Data Intelligence
Dr Ken Mardaneh
Unit Learning Outcomes covered in this assessment
Demonstrate advanced and integrated understanding of business and data Intelligence for organisational decision-making. Analyse critically, reflect on and synthesise techniques of data visualisation and data mining.
All work must be submitted on Moodle by the due date along with a completed AssignmentCoverSheet. For Melbourne students: use Melbourne Campus Submission link. For Sydney students: use Sydney Campus Submissions link. Reference sources must be listed appropriately at the end in a reference list using APA referencing style.
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Assessment Cover Sheet
Student ID Number/s:
Student Declaration I/We declare that: the work contained in this assignment is my/our own work/group work, except where acknowledgement of sources is made; certify that this assessment has not been submitted previously for academic credit in this or any other course; I/we have read the MIT’s Plagiarism and Academic Misconduct Policy Procedure, and I/we understand the consequences of engaging in plagiarism; a copy of the original assignment is retained by me/us and that I/we may be required to submit the original assignment to the Lecturer and/or Unit Co-ordinator upon request;I/we have not plagiarised the work of others or participated in unauthorised collaboration when preparing this assignment.
For Assessor Use Only (if not marked on Moodle)
The assignment is designed to allow you to demonstrate effective business analytics skills using optimisation methods. You will need to use linear programming skills to conduct the analytics and obtain the solutions. This is individual assignment and each student will work independently.
Problem 1: Three objective functions for linear programming problems are 7A+10B, 6A+4B, and -4A+7B. Show the graph of each for objective function values equal to 420. (5 marks)
Problem 2: Consider below the linear programming problem: (5 marks)
Constraint R.H. side
The value of the optimal solution is 27. Suppose that the right-hand side for consraint1 is increased from 10 to 11.
Use the graphical solution procedure to find the new optimal solution. (2 marks)
Use the solution to part (a) to determine the shadow price for constraint 1. (1 mark)
The sensitivity analysis for the linear program in this problem provides the following right-hand side range information:
What does the right-hand side range information for constraint 1 tell you about the shadow price for constraint 1? (1 mark)
The shadow price for constraint 2 is 0.5. Using this shadow price and the right-hand-side range information in part (c), what conclusion can you draw about the effect of changes to the right-hand side of constraint 2? (1 mark)
Problem 3: Maxwell Manufacturing makes two models of felt tip marking pens. Requirements for each lot of pens are given below. (5 marks)
The profit for either model is $1000 per lot.
What is the linear programming model for this problem (write objective function and constraints? (3 marks)
Show the solution graphically. (2 mark)
Let F= the number of lots of Fliptop pens to produceLet T= the number of lots of Tiptop pens to produce
Problem 4: For this problem: (5 marks)
Solve the following linear program graphically and, (2 marks)
Show the feasible region and, (2 mark)
Show the optimal point. (1 mark)
5X + 7Y
X ≤ 6
2X + 3Y ≤ 19
X + Y ≤ 8
X, Y ≥ 0
Note: Students need to submit the assignment as a word document.
MA609 Businessanalyticsand data Intelligence Assignment[Individual] Marking Guide (20 Marks)
Proper graphical representation of the models Comment:
Accurate measurement of the graphs Comment:
Identifying the feasible points Comment:
Identifying the feasible region Comment:
Identification of the range of optimality Comment:
Indication of improvement in the value of optimal solutions Comment:
Structure and Presentation of the assignment: Comment:
= _____/20__ Marks Date:
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