Contingency Workload Demand Forecast Techniques for Cargo ... contingency workload demand forecast techniques

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  • Air Force Institute of Technology AFIT Scholar

    Theses and Dissertations Student Graduate Works

    3-24-2016

    Contingency Workload Demand Forecast Techniques for Cargo and Flying Hours Calvin J. Bradshaw III

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    Recommended Citation Bradshaw, Calvin J. III, "Contingency Workload Demand Forecast Techniques for Cargo and Flying Hours" (2016). Theses and Dissertations. 356. https://scholar.afit.edu/etd/356

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  • CONTINGENCY WORKLOAD DEMAND FORECAST TECHNIQUES FOR CARGO AND FLYING HOURS

    THESIS

    CALVIN J. BRADSHAW III, Major, USAF

    AFIT-ENS-MS-16-M-093

    DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY

    AIR FORCE INSTITUTE OF TECHNOLOGY

    Wright-Patterson Air Force Base, Ohio

    DISTRIBUTION STATEMENT A. APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED.

  • The views expressed in this thesis are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the United States Government. This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States.

  • AFIT-ENS-MS-16-M-093

    CONTINGENCY WORKLOAD DEMAND FORECAST TECHNIQUES FOR CARGO AND FLYING HOURS

    THESIS

    Presented to the Faculty

    Department of Operational Sciences

    Graduate School of Engineering and Management

    Air Force Institute of Technology

    Air University

    Air Education and Training Command

    In Partial Fulfillment of the Requirements for the

    Degree of Master of Science in Operations Research

    Calvin J. Bradshaw III, M.E.M

    Major, USAF

    March 2016

    DISTRIBUTION STATEMENT A. APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED.

  • AFIT-ENS-MS-16-M-093

    CONTINGENCY WORKLOAD DEMAND FORECAST TECHNIQUES FOR

    CARGO AND FLYING HOURS

    Calvin J. Bradshaw III, M.E.M

    Major, USAF

    Committee Membership:

    Dr. Ray. R. Hill Chair

    Dr. Jeffery Weir Member

  • ii

    AFIT-ENS-MS-16-M-093

    Abstract

    Accurate forecasting of contingency workload demand for USTRANSCOM

    (USTC) is a herculean effort. Transportation Working Capital Fund (TWCF) managers

    rely on various subject matters outside and within the combatant command to estimate

    future workload. Since rates are set annually, when TWCF activities use incorrect or

    incomplete projections of workload, this leads to erroneous price structures and

    misaligned customer billing rates. The USTC leadership lacks the ability to accurately

    forecast workload demand, which is a key driver for service provider rate-setting. As a

    result, some customers perceive spiked rates and seek service from other competitors,

    which generates lost revenue, customer dissatisfaction and the inability to maximize

    workload to meet the readiness goals of the command.

    Time series forecasting is a technique planners use to model future demand. This

    paper examines a variety of time-series techniques applied to historical cargo and flying

    hour workload demand primarily from Air Mobility Command’s (AMC) contingency and

    special airlift assignment missions (SAAM). The goal is to develop a non-prescriptive

    guide to improve the rate setting process and enable USTC leadership to better manage

    combat capability. The research introduces a median-based forecast along with an

    anecdotal guide for anticipating future annual workload to more accurately inform the

    USTC budget.

  • iii

    Dedicated to my wonderful wife and children

  • iv

    Acknowledgments

    I sincerely appreciate the guidance of Lt Col Robert Nance, who greatly assisted me

    with the scope of the problem and served as my conduit to the data. I especially would like

    to thank Ray R. Hill, Ph.D., for his guidance and review of this effort along the way. Most

    importantly, thanks to my family for supporting my efforts to research and write.

    Maj Calvin J. Bradshaw III

  • v

    Table of Contents

    Table of Contents .................................................................................................................v

    List of Tables ..................................................................................................................... ix

    List of Figures ......................................................................................................................x

    I. Introduction .................................................................................................................14

    A. Background .......................................................................................................18

    B. Problem Statement and Issues ...........................................................................21

    C. Objective ...........................................................................................................22

    D. Hypothesis .........................................................................................................22

    E. Assumptions and Limitations ............................................................................23

    F. Current USTRANSCOM Workload Demand Forecast Process .......................23

    II. Literature Review .......................................................................................................26

    A. Forecasting Techniques .....................................................................................26

    i. Time Series Exploration (example) ...................................................................35

    ii. Time Series Regression .....................................................................................39

    iii. Decomposition ..................................................................................................49

    iv. Smoothing (weighted moving average) ............................................................52

    v. Box Jenkins .......................................................................................................54

    vi. Transfer Function ..............................................................................................61

    B. Summary ...........................................................................................................62

    III. USTC Cargo demand forecast....................................................................................63

    A. Background ......................................................................................................63

  • vi

    B. Time Series Plot ................................................................................................66

    C. Initial Regression analysis .................................................................................68

    D. Data sanitization ................................................................................................77

    E. Decomposition ..................................................................................................83

    F. Forecast model building ....................................................................................97

    i. Moving Average models ...................................................................................99

    ii. Smoothing models .............................................................................................99

    a. Simple Exponential Smoothing .........................................................................99

    b. Linear (Holt’s) Exponential ............................................................................100

    c. Double (Brown’s) Exponential .......................................................................101

    d. Damped-trend Linear Exponential ..................................................................102

    e. Seasonal Exponential ......................................................................................103

    f. Winters or