Assessing uncertainty and risk in an expeditionary military logistics network. (April 2021)

• Record Type: Journal Article
• Authors: McConnell, Brandon M; Hodgson, Thom J; Kay, Michael G; King, Russell E; Liu, Yunan; Parlier, Greg H; Thoney-Barletta, Kristin; Wilson, James R
• Is Part Of: Journal of defense modeling and simulation. Volume 18:Number 2(2021)
• Page Start: 135
• Page End: 156
• Publication Date: 2021-04
• Subjects: Logistics -- capacity planning -- queueing -- networks -- forecasting -- risk analysis -- nonstationary arrival process -- time-dependent arrival rate -- dispersion ratio -- index of dispersion for counts; Military art and science -- Computer simulation -- Periodicals; 355.0011305
• DOI: 10.1177/1548512919860595
• Languages: English
• ISSNs: 1548-5129

Abstract

Uncertainty is rampant in military expeditionary operations spanning high-intensity combat to humanitarian operations. These missions require rapid planning and decision-support tools to address the logistical challenges involved in providing support in often austere environments. The US Army's adoption of an enterprise resource planning system provides an opportunity to develop automated decision-support tools and other analytical models designed to take advantage of newly available logistical data. This research presents a tool that runs in near-real time to assess risk while conducting capacity planning and performance analysis designed for inclusion in a suite of applications dubbed the Military Logistics Network Planning System, which previously only evaluated the mean sample path. Logistical data from combat operations during Operation Iraqi Freedom drive supply requisition forecasts for a contingency scenario in a similar geographic environment. A nonstationary queueing network model is linked with a heuristic logistics scheduling methodology to provide a stochastic framework to account for uncertainty and assess risk.