About

Brandon McConnell is the Director of MEM and an Associate Research Professor at NC State's Edward P. Fitts Department of Industrial and Systems Engineering. His research focus includes areas related to manufacturing, systems, and engineering processes. As a faculty member, he contributes to the department's mission of advancing industrial engineering through research and education.

Research topics

• Computer Science
• Computer Security
• Engineering
• Operations research
• Operations management
• Aeronautics
• Economics
• Artificial Intelligence
• Political Science
• Mathematical optimization
• Reliability engineering
• Medicine
• Operating system
• Simulation
• Transport engineering
• Marketing
• Aerospace engineering
• Medical emergency
• Microeconomics
• Psychology
• Internal medicine
• Business
• Industrial engineering
• Systems engineering

Selected publications

• Military maritime load planning instances for prioritized two-dimensional orthogonal packing

  Open MIND · 2025-12-04

  datasetSenior author

  This dataset supports the computational validation of prioritized two-dimensional orthogonal packing algorithms applied to military combat loading scenarios, as detailed in "Enhancing Military Load Planning: A Prioritized 2-D Orthogonal Packing Approach". The repository comprises 70 problem instances derived from authoritative U.S. Army equipment databases, specifically the Joint Equipment Characteristic Database (JECD) and the Modified Table of Organizational Equipment (MTOE) for a representative Armored Brigade Combat Team (ABCT). The data represents approximately two brigades of equipment filtered for roll-on/roll-off capability—including tracked combat vehicles, self-propelled artillery, and heavy wheeled vehicles—to simulate realistic amphibious embarkation requirements. Instances are provided in JSON format and categorize items by Unit Identification Code (UIC) and Paragraph Number (PARNO) to enforce hierarchical packing priorities that balance access-point proximity with unit cohesion. The dataset spans six representative vessel classes (Whidbey Island, Wasp, Harpers Ferry, Besson, America, and Runnymede) with target space utilization levels ranging from 65% to 85%. Supplementary Julia scripts utilizing the Gurobi optimizer are included to reproduce computational experiments across three solution methods: a monolithic Mixed-Integer Linear Program (MILP), a standard sliding-window matheuristic, and an in-stride balancing variant. These scripts evaluate algorithmic performance against strict center-of-gravity deviation tolerances (δ∈{0.01,0.05,0.10,0.15}), enabling the assessment of trade-offs between load balancing feasibility, solution quality, and computational efficiency.

  DOI

• Evaluating the implementation of operational readiness and maintenance policies in US Army aviation

  The Journal of Defense Modeling and Simulation Applications Methodology Technology · 2025-03-25

  articleSenior author

  This study examines AH-64 Apache dispatch decisions to assess the implementation of operational readiness (OR) and maintenance policies in the US Army. Current policies are designed to promote a ready and flexible force that is prepared to respond to global force projection requirements. The Army dictates a 75% OR target for aviation equipment and urges units to utilize aircraft uniformly to distribute maintenance capacity and prevent backlog. Given these objectives, we would expect a reduced OR rating to compel fewer sorties and uniformly distributed flying hours over the phase maintenance horizon. However, using a generalized additive model (GAM), findings indicate that diminished OR does not deter flight operations. Moreover, aircraft are more likely to be grounded when approaching scheduled phase maintenance. Further analysis exposes a significant interaction effect; units place greater weight on an aircraft’s hours until phase maintenance in the presence of low OR, highlighting a potential risk aversion in decision-making. Interestingly, control variables (the day of the week and reporting period proximity) highly correlate with flight decisions. The findings suggest that current aviation readiness metrics may have an unintended influence on units’ resource allocation. Future research should investigate unit-specific decision-making frameworks to improve aviation maintenance and OR efficiency.

  PublisherDOI

• Air movement operations planning heuristic improvement

  Journal of Defense Analytics and Logistics · 2025-01-16

  articleOpen accessCorresponding

  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.

  PublisherOA PDFDOI

• Evaluating the Implementation of Operational Readiness and Maintenance Policies in US Army Aviation

  2025-02-10

  preprintOpen accessSenior author

  This study examines AH-64 Apache dispatch decisions to assess the implementation of Operational Readiness (OR) and maintenance policies in the US Army. Current policies are designed to promote a ready and flexible force that is prepared to respond to global force projection requirements. The Army dictates a 75% OR target for aviation equipment and urges units to utilize aircraft uniformly to distribute maintenance capacity and prevent backlog. Given these objectives, we would expect a reduced OR rating to compel fewer sorties and uniformly distributed flying hours over the phase maintenance horizon. However, using a Generalized Additive Model (GAM), findings indicate that diminished OR does not deter flight operations. Moreover, aircraft are more likely to be grounded when approaching scheduled phase maintenance. Further analysis exposes a significant interaction effect; units place greater weight on an aircraft’s hours until phase maintenance in the presence of low OR, highlighting a potential risk aversion in decision-making. Interestingly, control variables (the day of the week and reporting period proximity) highly correlate with flight decisions. The findings suggest that current aviation readiness metrics may have an unintended influence on units' resource allocation. Future research should investigate unit-specific decision-making frameworks to improve aviation maintenance and OR efficiency.

  PublisherOA PDFDOI

• Implementing Trades of the National Football League Draft on Blockchain Smart Contracts

  2025-02-24 · 1 citations

  preprintOpen access

  Purpose - Demonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts. Design/Methodology/Approach - Using Ethereum smart contracts, we model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results. Findings - We show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally. Originality/value - This research demonstrates the new application of smart contracts in the intersection of sports management and blockchain technology. Research limitations/implications - Further work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience. Practical implications - Cutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost. Social Implications - Full-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams.

  PublisherOA PDFDOI

• The 2-D Orthogonal Packing Problem with Multiple Levels of Prioritization: A Spatial Optimization Perspective

  2025-05-23

  preprintOpen accessSenior author

  This paper addresses two-dimensional orthogonal packing within a confined space, integrating bin packing principles with facility layout concepts to address scenarios in which items must not only fit but also be arranged according to spatial priorities. We embed a prioritization matrix into the bin packing framework, enabling items to be clustered with one another or pulled toward certain bin access points based on assigned priority weights. Unlike traditional bin packing, which focuses on space utilization alone, our approach balances proximity to bin access points and adjacency among functionally related items, extending the utility of bin packing to applications requiring more nuanced layout preferences. We introduce a single mixed-integer linear programming (MILP) model and a complemen- tary sliding-window matheuristic that scales effectively to larger problem instances. Numerical experiments illustrate that this matheuristic approach consistently outperforms a direct MILP solve with a commercial solver in both runtime and solution quality, and also performs best among the adapted heuristic and metaheuristic alternatives considered in our study. This computational study underscores the flexibility and effectiveness of embedding multi-level priorities into orthogonal packing.

  PublisherOA PDFDOI

• Enhancing Military Load Planning: A Prioritized 2-D Orthogonal Packing Approach

  2025-12-20

  articleOpen accessSenior author

  Military combat loading requires arranging equipment on maritime transport vessels to enable rapid, prioritized off-loading while maintaining unit cohesion and vessel stability. This paper extends a prioritized two-dimensional orthogonal packing framework to address the specific operational constraints of military logistics, incorporating global load balancing requirements alongside existing prioritization objectives. We introduce three solution techniques for this globally constrained problem: a monolithic mixed-integer linear programming (MILP) approach, a sliding-window matheuristic, and a sliding-window matheuristic with in-stride load balancing penalties. For any sliding-window solution that fails to achieve both feasible packing and load balancing in the initial stage, we develop a universal post-processing strategy that selectively relaxes and re-optimizes item positions to achieve balance with minimal disruption to the prioritized layout. Computational experiments demonstrate that the matheuristic approaches fundamentally outperform the monolithic MILP approach in load balance reliability, solution quality, and computational efficiency, providing practical guidance for integrating automated optimization into military load planning systems. The proposed methods generate high-quality, load-balanced solutions for single-vessel scenarios in approximately two minutes on average, enabling rapid evaluation of multiple loading configurations during time-critical deployment planning.

  PublisherOA PDFDOI

• Identifying Best Performance Scenarios For Micro Nuclear Reactors During Grid Disruption

  2024-11-04

  articleOpen accessSenior author

  Micro Nuclear Reactors (MNRs) are an emerging innovation in nuclear technology as small, portable, and self-sufficient reactor units in the size of a standard 40-foot shipping container. An MNR functions as a "nuclear battery," where each unit can power load capacities from 500 kilowatts (kW) to 5 megawatts (MW) over the lifetime of 1–10 years. This technology may deploy by the end of the 2020 decade, so private and government organizations have prepared for potential operational use for energy resilience. This research develops an emergency grid disruption timeline with MNR deployments to respond and recover grids after severe weather events. This response integrates a series of models for transportation networks, power distribution, and decision strategies that utilize MNR capabilities while using real-world disruption events within the past decade for scenarios. The study then seeks to analyze the performance of MNRs when using different deployment strategies for emergency grid disruption response. First, this research investigates the trade-offs between time and cost in the emergency grid disruption timeline when integrating MNRs. This research also explores the conditions of disruption scenarios that contribute to the best MNR performance in grid recovery.

  PublisherOA PDFDOI

• Implementing trades of the National Football League Draft on blockchain smart contracts

  International Journal of Sports Marketing and Sponsorship · 2024-01-12 · 4 citations

  article

  Purpose Demonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts. Design/methodology/approach Using Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results. Findings The authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally. Research limitations/implications Further work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience. Practical implications Cutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost. Social implications Full-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams. Originality/value This research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.

  PublisherDOI

• Automatic Feature Based Inspection and Qualification for Additively Manufactured Parts with Critical Tolerances

  2024-12-27

  preprintOpen accessSenior author

  This work expands the capabilities of the Digital Additive and Subtractive Hybrid (DASH) system by including "geometric qualification" of mechanical products. Specifically, this research incorporates the extended Additive Manufacturing Format files (AMF-TOL) which include American Society of Mechanical Engineers (ASME) Y14.5 specifications for planes, cylinders and other features so that "in-process" inspection can be completed automatically. An example for the production of hols is provided to illustrate On-Machine-Measurement collects sample radii to estimate the size and position of finished cylindrical features. Statistical analysis was used to measure bounds for comparison to specified tolerance callouts to determine whether a part is within specification, within a user-defined level of confidence. Seven different sampling strategies were evaluated on a DASH part including the bird cage sampling strategy defined in ISO-12180. Part data was utilized to show that for large data samples no statistically significant difference in accuracy was identified for four methods. Finally, analysis shows that using the DASH process with automatic inspection is economically advantageous for low volume production runs.

  PublisherOA PDFDOI

Frequent coauthors

• Michael G. Kay

  North Carolina State University

  28 shared

• Russell E. King

  North Central State College

  28 shared

• Kristin Thoney-Barletta

  22 shared

• Thom J. Hodgson

  North Carolina State University

  16 shared

• Ryan D. Winz

  U.S. Air Force Institute of Technology

  9 shared

• Jack Werner

  8 shared

• James R. Wilson

  North Carolina State University

  7 shared

• Russell Nelson

  6 shared

Education

• PhD, Operations Research, Operations Research Graduate Program

  North Carolina State University

  2018

• Master of Operations Research (MOR), Operations Research Graduate Program

  North Carolina State University

  2015

• Operations Research (BS), Department of Mathematical Sciences

  United States Military Academy

  2006

Awards & honors

• Richard H. Barchi Prize for Best Paper, Military Operations…
• Award for Excellence in Classroom Teaching, NC State Univers…
• ISE Outstanding Teaching Assistant Award, NC State ISE Depar…
• Edward A. Shook Mentor Award, NC State ISE Department (2018)
• Recognition for Excellence in Mentorship, NC State Universit…