Reference no: EM132307759

Real World Analytics Assignment -

Learning Outcomes -

• Assessed through student ability to apply game theory, and linear programming skills and models, to make optimal decisions.
• Assessed through student ability to develop software codes to solve computational problems for real world analytics.

Purpose - Assignment assesses your abilities to build linear programming models and solving them. You will demonstrate your skills in using linear programming to model real life case studies. You will consider cases with two variables and solve them using the graphical method. For problems with more than two variables, you will solve the linear programming models that you built using linear programming solvers in appropriate software, such as R. You will consider game theory - two players zero sum game - to build appropriate models that describe different game scenarios. You will demonstrate your knowledge in investigating the existence of equilibrium (stable solution). You will use mixed models to find appropriate solutions and solve the models you constructed with appropriate software such as R.

Assessment Task - Problem Solving

The assessment consists of THREE question sets. Students must attempt all tasks and provide an individual written report in appropriate word processor.

Q1. A food factory is making a beverage for a customer from mixing two different existing products A and B. The compositions of A and B and prices ($/L) are given as follows,

	Amount (L) in / 100 L of A and B
	Lime	Orange	Mango	Cost ($/L)
A	3	6	4	8
B	8	4	6	7

The customer requires that there must be at least 4.5 Litres (L) Orange and at least 5 Litres of Mango concentrate per 100 Litres of the beverage respectively, but no more than 6 Litres of Lime concentrate per 100 Litres of beverage. The customer needs at least 70 Litres of the beverage per week.

a) Explain why a linear programming model would be suitable for this case study.

b) Formulate a Linear Programming (LP) model for the factory that minimises the total cost of producing the beverage while satisfying all constraints.

c) Use the graphical method to find the optimal solution. Show the feasible region and the optimal solution on the graph. Annotate all lines on your graph. What is the minimal cost for the product?

Note: you can use graphical solvers available online but make sure that your graph is clear, all variables involved are clearly represented and annotated, and each line is clearly marked and related to the corresponding equation.

d) Is there a range for the cost ($) of A that can be changed without affecting the optimum solution obtained above?

Q2. A factory makes three products called Spring, Autumn, and Winter, from three materials containing Cotton, Wool and Silk. The following table provides details on the sales price, production cost and purchase cost per ton of products and materials respectively.

	Sales price	Production cost		Purchase price
Spring	$60	$5	Cotton	$30
Autumn	$55	$4	Wool	$45
Winter	$60	$5	Silk	$50

The maximal demand (in tons) for each product, the minimum cotton and wool proportion in each product is as follows:

	Demand	min Cotton proportion	min Wool proportion
Spring	4500	50%	30%
Autumn	4000	60%	40%
Winter	4000	40%	50%

a) Formulate an LP model for the factory that maximises the profit, while satisfying the demand and the cotton and wool proportion constraints.

b) Solve the model using R/R Studio. Find the optimal profit and optimal values of the decision variables.

Q3. Helen and David are playing a game by putting chips in two piles (each player has two piles P1 and P2), respectively. Helen has 6 chips and David has 5 chips. Each player places his/her chips in his/her two piles, then compare the number of chips in his/her two piles with that of the other player's two piles. Note that once a chip is placed in one pile it cannot be moved to another pile. There are four comparisons including Helen's P1 vs David's P1, Helen's P1 vs David's P2, Helen's P2 vs David's P1, and Helen's P2 vs David's P2. For each comparison, the player with more chips in the pile will score 1 point (the opponent will lose 1 point). If the number of chips is the same in the two piles, then nobody will score any points from this comparison. The final score of the game is the sum score over the four comparisons. For example, if Helen puts 5 and 1 chips in her P1 and P2, David puts 4 and 1 chips in his P1 and P2, respectively. Then Helen will get 1 (5 vs 4) + 1 (5 vs 1) - 1 (1 vs 4) + 0 (1 vs 1) = 1 as her final score, and David will get his final score of -1.

(a) Give reasons why/how this game can be described as a two-players-zero-sum game.

(b) Formulate the payoff matrix for the game.

(c) Explain what is a saddle point. Verify: does the game have a saddle point?

(d) Construct a linear programming model for each player in this game.

(e) Produce an appropriate code to solve the linear programming model in part (c).

(f) Solve the game for David using the linear programming model you constructed in part (c). Interpret your solution.

Attachment:- Assignment File.rar