Game-Theoretic Models for Rapid Operational Airlift Network Design in Contested Environments

Abstract

The growing threat of conflict with near-peer adversaries requires a robust air-routing plan to transport personnel and cargo effectively. In developing these plans, the U.S. Air Forces Air Mobility Command (AMC) must account for the dynamic nature of inter-theater operations in a contested environment. Currently, AMC planners predominantly calculate resource allocations manually, which contributes to slower plan implementation and potentially suboptimal solutions. Starting with a proven AMC model, which provides an optimal use of aircraft, cargo allocation, and airfields, we add model features that help determine how to attack this airlift network, optimally delaying the delivery of cargo to operationally relevant locations. The results identify vulnerabilities and provide AMC planners with a prescription of airfield resource allocation that maximizes the movement of cargo. This model delivers a quantitative assessment of an adversary's (whether weather or competitor) ability to delay the mission that can be used to guide policymakers in providing a robust air mobility capability.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2023
Accession Number
AD1212898

Entities

People

  • Alexander J. Cooper

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Aircrafts
  • Algorithms
  • Cargo Aircraft
  • Contested Environments
  • Department Of Defense
  • Geographic Regions
  • International Airports
  • Linear Programming
  • Military Operations
  • National Security
  • Operations Research
  • Security
  • South Korea
  • Transport Aircraft
  • Transportation
  • Unified Combatant Commands
  • United States
  • United States Transportation Command

Readers

  • Aerospace logistics and air mobility.
  • Maritime Combat Support and Expeditionary Logistics.
  • Operations Research