Air movement operations planning heuristic improvement

Purpose The purpose of this paper is to improve the air movement operations planning heuristic in the literature to generate better solutions in a shorter time period. Design/methodology/approach Through a rigorous design of experiments (DOEs), we make significant heuristic improvements by evaluating alternative modular methodologies and tuning heuristic parameters for two scenarios. This includes a new approach to considering refueling operations. Findings We find the fine-tuned heuristic averages a 33% objective improvement and 70% reduction in computation time over the heuristic with original parameters for one of the scenarios. Additionally, we analyze the heuristic's quality of solution over time. Research limitations/implications Further analysis is required to generalize heuristic settings, which would require significant access to operational data or a portfolio of scenarios of interest. Practical implications Tuned heuristic parameters reduce the computation time from hours to minutes. This also makes it practically feasible to adjust parameters in the objective function to generate multiple courses of action (COAs) for a given instance. Originality/value This research provides novel vehicle assignment and routing heuristic improvement alternatives and demonstrates a DOEs-based heuristic tuning procedure.

Authors

Institutions

Publication Details

Journal
Journal of Defense Analytics and Logistics
Published
2025-01-16
DOI
https://doi.org/10.1108/jdal-02-2024-0003
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Air movement operations planning heuristic improvement

Jack Werner, Kristin Thoney-Barletta, Rebecca Daniels, Russell E. King et al.
Journal of Defense Analytics and Logistics
Advanced Manufacturing and Logistics Optimization
article

Air movement operations planning heuristic improvement

Jack Werner, Kristin Thoney-Barletta, Rebecca Daniels, Russell E. King, Michael G. Kay, Russell Nelson, Brandon M. McConnell
article en

Abstract

Purpose The purpose of this paper is to improve the air movement operations planning heuristic in the literature to generate better solutions in a shorter time period. Design/methodology/approach Through a rigorous design of experiments (DOEs), we make significant heuristic improvements by evaluating alternative modular methodologies and tuning heuristic parameters for two scenarios. This includes a new approach to considering refueling operations. Findings We find the fine-tuned heuristic averages a 33% objective improvement and 70% reduction in computation time over the heuristic with original parameters for one of the scenarios. Additionally, we analyze the heuristic's quality of solution over time. Research limitations/implications Further analysis is required to generalize heuristic settings, which would require significant access to operational data or a portfolio of scenarios of interest. Practical implications Tuned heuristic parameters reduce the computation time from hours to minutes. This also makes it practically feasible to adjust parameters in the objective function to generate multiple courses of action (COAs) for a given instance. Originality/value This research provides novel vehicle assignment and routing heuristic improvement alternatives and demonstrates a DOEs-based heuristic tuning procedure.

Journal of Defense Analytics and Logistics
North Carolina State University (US), United States Military Academy (US)
U.S. Department of Defense
Openalex Percentile: Top 99%
Advanced Manufacturing and Logistics Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Air movement operations planning heuristic improvement — Jack Werner, Kristin Thoney-Barletta, et al. · Journal of Defense Analytics and Logistics (2025) | TGRS Research Map | TGRS