**04-73-331: Case 1**

**10.08.2014**

Introduction - problem, importance

Analysis - approach, methods, results

Conclusion - recommendations

AGENDA

INTRODUCTION

METHOD 1

METHOD 2

Wai Ting Yip

**103799986**

**Garet Duggal**

**103803094**

**Evan Dierickse**

**103830207**

**Nick Fenos**

**103853022**

**Aira Ladia**

**103752738**

Shawn Phaneuf

**103801474**

METHOD 3

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

CONCLUSION

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

**103845001**