Multiple Attribute Decision Making

STEW-MOD1-SLP-520- MADM TABLE
Name
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Multiple attribute decision making
  CriteriaNPV Traffic count Bldg. size (sq ft. 000)Lot sizeInsuranceAccessTotal Aggregate  ($000,000) ($000 / yr) Score      Location    Abberton1,200,00011,000300045,0005,10011,247,9001.25Bellview2,300,00015,0003,10050,0005,6000.672,356,3001.67Casstown1,600,00010,0002,90040,0005,5000.671,641,6001.17Denton1,100,00012,0003,60055,0006,4000.331,157,0000.33Eddington2,000,00016,0004,00060,0006,30002,065,7000.75
Based on the assumption that the traffic count, building size, lot size and insurance cost all have a cost of $ 1,000 then it is possible to aggregate the information for these criteria and then summing up with the access criterion. Assuming that the highest value has a value of 1, the next values are then ranked with 0.75, 0.5, 0.25 and 0. However in the case of access there are four options available unlike the others where there are 5 different scenarios. Consequently, the ranking are 1 for the highest which is excellent, 0.67 for good, 0.33 for fair and 0 for poor. Hence, aggregating the sum of other five criteria with that of the access gives a total score to facilitate in decision making. Consequently the Abberton location is chosen as the best option through looking into the multiple attributes.
Bellview
For the six criteria the first five were viewed together, while the sixth was fist analyzed alone since there were four options for each of the locations. Furthermore, it is a subjective matter that cannot be quantified to determine the likely of accessibility. The close to drive through traffic taking into account the average thousands per day was necessary to determine the effects of the location. As such the highest score was 1 while the lowest was 0 depending on the closeness to drive through traffic. The aggregation of individual criteria rankings is necessary to give weights to the criteria depending on the ranking, based on the assumption that there is a linear relationship between the rank and weight (Alfares & Duffuaa, 2008).
According to Zavadskas et al (2008), in making a decision one ought to follow rational behavior and where possible taking into account the effect on utility in various alternatives. This then makes it easier to give advice based on the decision- making analysis. In the case, the alternative locations in Columbus, Ohio are all viable when looking at one criterion, but since only one optimal alternative is preferred, then one is chosen as the final decision. Ideally based on the decision analysis it is expected that the preferred alternative will be preferred. However, in case the...