Robert M. Curry
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor
Also affiliated: United States Naval Academy (2021); Clemson University (2016–2017)
Faculty Researcher
Research Areas
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Biography and Research Information
OverviewAI-generated summary
Robert M. Curry's research focuses on the development and application of mixed-integer programming models and optimization techniques. His work addresses complex scheduling and resource allocation problems across various domains. Curry has investigated minimum-cost flow problems with arc-activation costs and developed augmenting-flow algorithms for node-capacitated maximum flow problems. His recent publications explore mixed-integer programming models for dynamic network flow scheduling and coordinated multi-vector attack graph problems, including the application of logic-based Benders decomposition methods. He has also contributed to an All-Hazards Return on Investment (ROI) model for evaluating U.S. Army installation resilient strategies and examined optimal island occupation strategies. Curry's scholarship includes 12 publications with 112 citations and an h-index of 3. He collaborates with researchers at the University of Arkansas at Fayetteville, including Zephan Wade, Gregory S. Parnell, and Eric Specking.
Metrics
- h-index: 3
- Publications: 12
- Citations: 113
Selected Publications
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Mixed-integer programming models and a logic-based Benders decomposition method for solving coordinated multi-vector attack graph problems (2026)
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An All-Hazards Return on Investment (ROI) Model to Evaluate U.S. Army Installation Resilient Strategies (2025)
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Mixed-Integer Programming Modeling Strategies for Scheduling-Based Optimization Problems (2024)
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Mixed-integer programming models and heuristic algorithms for the maximum value dynamic network flow scheduling problem (2024)
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Practice Summary: Optimal Student Group Reassignment at U.S. Naval Academy (2023)
Collaboration Network
Top Collaborators
- Mixed-integer programming models and heuristic algorithms for the maximum value dynamic network flow scheduling problem
- Mixed-integer programming models and a logic-based Benders decomposition method for solving coordinated multi-vector attack graph problems
- Practice Summary: Optimal Student Group Reassignment at U.S. Naval Academy
- Practice Summary: Optimal Student Group Reassignment at U.S. Naval Academy
- Practice Summary: Optimal Student Group Reassignment at U.S. Naval Academy
- Mixed-integer programming models and heuristic algorithms for the maximum value dynamic network flow scheduling problem
- Mixed-Integer Programming Modeling Strategies for Scheduling-Based Optimization Problems
- An All-Hazards Return on Investment (ROI) Model to Evaluate U.S. Army Installation Resilient Strategies
- An All-Hazards Return on Investment (ROI) Model to Evaluate U.S. Army Installation Resilient Strategies
- An All-Hazards Return on Investment (ROI) Model to Evaluate U.S. Army Installation Resilient Strategies
- An All-Hazards Return on Investment (ROI) Model to Evaluate U.S. Army Installation Resilient Strategies
- An All-Hazards Return on Investment (ROI) Model to Evaluate U.S. Army Installation Resilient Strategies
- An All-Hazards Return on Investment (ROI) Model to Evaluate U.S. Army Installation Resilient Strategies
- An All-Hazards Return on Investment (ROI) Model to Evaluate U.S. Army Installation Resilient Strategies
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