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04-73-331: Case 1

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Wai Ting Yip

on 8 October 2014

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Transcript of 04-73-331: Case 1

04-73-331: Case 1
Introduction - problem, importance
Analysis - approach, methods, results
Conclusion - recommendations
Wai Ting Yip
Garet Duggal
Evan Dierickse
Nick Fenos
Aira Ladia
Shawn Phaneuf
Gotham International Airport
9/11 - Transportation Security Administration (TSA)
Improve airport security procedures while reducing passenger waiting times
determine how many security checkpoints are needed
develop a forecast for daily passenger arrivals
Passenger arrivals for 10 days (July)
STEP 1: simplify the data by seperating the data into years and find the averages of each
STEP 2: find the seasonal factors
STEP 3: find slope and intercept to make the equation y=5490x+11653
STEP 4: find the linear trend forecast
STEP 5: Find the seasonally adjusted forecasts
STEP 2: slope and intercept to find equations
STEP 3: find forecasts
STEP 1: compute four period moving average
STEP 2: compute the centred moving averages
STEP 3: Compute ratio of passengers over the corresponding centred MA
STEP 4: Average the factors corresponding to the same period
STEP 5: Scale up or down each factor so that the seasonal factor add up to N, the length of season
STEP 7: Find slope and intercept of deseasonalized series, forecast deseasonalized demand and reasonalize
STEP 6: Deseasonalize; divide each demand by the seasonalilty factor
STEP 1: find average of each time period for each year
STEP 2: find average number of passengers
STEP 3: find seasonality factor
STEP 4: find forecast
Tyler Bellaire
Method 1: Linear Regression and Seasonal Forecast
Method 2: The Multiplicative Seasonal Method
Method 3: Decomposition Using Moving Averages
Full transcript