Research

Sabahattin Gokhan Ozden’s research interests have evolved around the application of optimization in complex simulation problems. He has participated in several private industry and government funded projects including Department of Defense, National Science Foundation, NASA, Materials Handling Institute, Missile Defense Agency, Steelcase, BORBET Group. He has co-authored a paper published in 2010 International Material Handling Research Colloquium proceedings, a journal paper submitted to Computers and Operations Research, and several working papers in the area of warehouse layout optimization, car sequencing, supply chain sustainability, and path findng which are targeted to be published in Transportation Research Part E, European Journal of Operational Research, and IIE Transactions.

  • Facility Logistics
  • Assembly Line Sequencing
  • Model Driven Engineering
  • Parallel & Distributed Computing
  • Supply Chain Sustainability

Research Projects

  • RT 159: Agile Systems Engineering Management

    RT 159: Agile Systems Engineering Management

    Modeling Agent Based Simulations for Systems Engineering Management

    Responsible for enhancing a domain-specific language and agent based simulation model for systems engineering
    Funded by Office of the Secretary of Defense/National Security Agency

  • A Model-Driven Generative Domain Architecture for Simulation Experiment Lifecycle Management and Systems Optimization

    A Model-Driven Generative Domain Architecture for Simulation Experiment Lifecycle Management and Systems Optimization

    Developing Domain Specific Optimization Languages for Experiment Management

    We demonstrated two heuristic optimization languages to optimize a quadcopter Simulink model for certain control parameters only using domain specific language without any knowledge in Java.

  • Non-traditional Designs for Order Picking Warehouses

    Non-traditional Designs for Order Picking Warehouses

    We optimize warehouse layouts for different order picking operations using in-house developed simulation and optimization techniques

    Order picking warehouse layouts have been the same for the last sixty years. We analyze if there are better layouts for order picking operations using simulation and optimization techniques.