Reza Mirjalili

I am a Ph.D. candidate at the University of Houston working in System Optimization and Computing Laboratroy (SOCL) under supervison of Prof. Gino J. Lim , specializing in operations research, combinatorial optimization, and machine learning for logistics systems. My research focuses on developing exact and intelligent algorithms to solve large-scale network design and routing problems with a particular emphasis on drone-assisted delivery systems. I have experience designing branch-and-price-and-cut frameworks, integrating reinforcement learning with optimization, and accelerating shortest path subroutines under complex constraints. My work spans both theoretical modeling and computational implementations in Rust, C, C++, Python, and Cython.

Research Interests

I work at the intersection of optimization, algorithm design, and AI, targeting scalable decision-making systems for logistics and transportation. My work focuses on combinatorial optimization, exact algorithms, and intelligent heuristics, with applications in both deterministic and stochastic logistics and transportation systems. I develop scalable, intelligent exact methods—such as branch-and-price-and-cut—employing DRL-assisted column and cut generation to solve complex routing and scheduling problems. My current research explores the integration of deep learning and mathematical optimization for multi-echelon vehicle routing and drone-assisted delivery networks.

• Vehicle Routing & Drone Coordination in hybrid delivery networks
• Branch-and-Price-and-Cut (BPC) for path-based routing problems
• Shortest Path with Resource Constraints (ESPPRC) using bidirectional labeling through DRL-based label propagation
• Cutting Plane Generation, e.g., Chvátal-Gomory and cycle-elimination cuts and hybrid cutting plane
• Reinforcement Learning for Optimization (pricing, branching, cuts)
• AI-Guided Subproblem Prioritization in column generation