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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Machine Learning Prediction Of Dod Personal Property Shipment Costs, Tiffany Tucker [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals
Machine Learning Prediction Of Dod Personal Property Shipment Costs, Tiffany Tucker [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals
Faculty Publications
U.S. Department of Defense (DoD) personal property moves account for 15% of all domestic and international moves - accurate prediction of their cost could draw attention to outlier shipments and improve budget planning. In this work 136,140 shipments between 13 personal property shipment hubs from April 2022 through March 2023 with a total cost of $1.6B were analyzed. Shipment cost was predicted using recursive feature elimination on linear regression and XGBoost algorithms, as well as through neural network hyperparameter sweeps. Modeling was repeated after removing 28 features related to shipment hub location and branch of service to examine their influence …
Forecasting Us Army Enlistment Contract Production In Complex Geographical Marketing Areas, Joshua L. Mcdonald, Edward D. White, Raymond R. Hill, Christian Pardo
Forecasting Us Army Enlistment Contract Production In Complex Geographical Marketing Areas, Joshua L. Mcdonald, Edward D. White, Raymond R. Hill, Christian Pardo
Faculty Publications
Purpose: The purpose of this paper is to demonstrate an improved method for forecasting the US Army recruiting. Design/methodology/approach: Time series methods, regression modeling, principle components and marketing research are included in this paper. Findings: This paper found the unique ability of multiple statistical methods applied to a forecasting context to consider the effects of inputs that are controlled to some degree by a decision maker. Research limitations/implications: This work will successfully inform the US Army recruiting leadership on how this improved methodology will improve their recruitment process.
Practical implications: Improved US Army analytical technique for forecasting recruiting goals.