Research

The School of Modeling, Simulation & Training

Research Overview

The OptiSim Lab conducts interdisciplinary research combining optimization, simulation, AI/ML, and digital-twin technologies to address large-scale, high-complexity decision problems.

Research Focus

  • Optimization & Operations Research
  • Simulation Modeling & Analysis
  • Digital Twins & Real-time Data Assimilation
  • AI/ML for Complex Systems

Primary Research Areas

1. Optimization & Operations Research

Focusing on planning and scheduling, multi-objective optimization, heuristic and metaheuristic algorithm design, and data-driven decision models. Dr. Rabadi is a globally recognized expert in these areas and serves as Chief Editor of the International Journal of Planning and Scheduling.

2. Simulation Modeling & Analysis

Using discrete-event, agent-based, and hybrid simulations to evaluate system performance under uncertainty. This aligns directly with the SMST’s strong emphasis on simulation-driven research.

3. Digital Twins & Real-time Data Assimilation

Developing digital-twin frameworks for disaster logistics, transportation systems, and cyber-physical operations that are supported by recent research in digital twins, adaptive systems, and data-driven modeling.

4. AI/ML for Complex Systems

Applying machine learning and intelligent analytics to improve predictive accuracy, enable real-time decision-making, and support resilient operations for critical infrastructure.

Application Domains

  • Supply chain modeling and optimization
  • UAV-based delivery systems & autonomous operations
  • Humanitarian logistics & disaster response
  • Aviation and runway scheduling
  • Smart cities & logistics digital twins

These domains reflect a long history of funded research from NASA, DHS, NATO, the U.S. Department of Education, and more.

Collaborate With Us

We partner with government, industry, and academic teams on applied R&D, student mentorship, and technology transition. Prospective students and collaborators are welcome to connect through OptiSim@ucf.edu.

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