Please check out ppt below for learning objective. I have 4 assignments but only done 1. Please help me with the other 3.

HW1: (this homework is done)

Use Affordability, Quality, and Style as the only Values for your decision in finding the best computer for you among 3 computers you have identified as your choices. Apply the Multifactor Evaluation Process by:

(i)assigning normalized weights to the Values,

(ii)assigning for each Value, ratings of individual computers, and normalizing these ratings for each Value.

(iii)computing the total score of each computer by multiplying the normalized weight to the normalized rating of each Value and summing the products for each Computer. Note: the total scores are automatically normalized, i.e., summing to 1.

The computer with the highest total score is the Best computer.

You must follow the example on OV-13 in the Course Overview PowerPoint slides to systematically show all normalized numerical results to receive full credits.

Answer for HW1:

WT

Affordability: 0.25

Quality: 0.6

Style: 0.15

Lenovo: 6/18=0.33 9/24=0.38 8/20=0.4 Total Score: 0.37

HP: 7/18=0.39 7/24=0.29 5/20=0.25 ToTal Score: 0.31

Dell: 5/18=0.28 8/24=0.33 7/20=0.35. Total Score: 0.32

HW2: Apply Analytic Hierarchy Process (AHP) to estimate the relative importance of Affordability, Quality, and Style in your selection of a computer. Specifically, your need to do the following:

(1) Based on AHP, set up a 3×3 pairwise comparison matrix of the 3 values, normalize it, and compute the row averages.

(2) Compute the largest eigenvalue and consistency index CI of the matrix.

(3) If CI is exactly 0, then the matrix is totally consistent. If CI is not 0, then use your subjective judgment to identify the weakest or least confident pairwise comparison and change it to conform to the other two pairwise comparisons you have made, so that the matrix becomes totally consistent.

(4) Compute the row averages for the totally consistent matrix which are the new weights for the 3 values based on AHP. Compute the ratio of the largest row average to the smallest row average and compare this ratio to the ratio of the largest weight to the smallest weight of the 3 values in your HW1, and indicate which ratio is greater or the weights are more differentiated (Note: use the weights of the 3 values NOT the total scores of the 3 computers) and do the same comparison for the ratio of the largest weight to the second largest weight of the 3 values in this homework and HW1.

HW3: Apply AHP to the full problem of finding the best computer for you, the decision-maker.

(1) (15 points) Follow the example on p.15 of the AHP power-point slides and construct the pairwise comparison matrix for your 3 candidate computers for each of the 3 values, compute the row averages, the largest eigenvalue, and the consistency index (CI) for each matrix.

If CI <=0.05, then you can use the row averages of the new matrix as the new normalized ratings for the 3 computers with respect to this value.

If CI>0.05, then you must modify the matrix to total consistency by making the pairwise comparison that is the weakest or least confident based on your subjective judgment to be totally consistent with the other two comparisons.

(2) (5 points) Follow the example on p.16 of the AHP power-point slides and use the AHP-based weights of the values from your HW2 and the AHP-based ratings of the computers under each value obtained in (1) to compute the total scores of the three computers and ratios of the largest to the smallest total scores and the largest to the second largest total scores. Compare these ratios with those you obtained from Multifactor Evaluation in HW1 to see whether the AHP-based ratios are larger and thus more differentiated.

HW4: For 4 choices A, B, C, and D, a decision-maker has the following pair-wise comparison matrix and rankings of the confidence in their validity:

A B C D (1) A vs. D Highest

A 1 1/2 1/4 1/8 (2) B vs. C

B 1 3 5 (3) C vs. D

C 1 1/2 (4) A vs. C

D 1 (5) A vs. B

(6) B vs. D Lowest

Use the rankings as the basis to make the matrix totally consistent.

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