SIMULATION OPTIMIZATION: NEW APPROACHES TO GRADIENT-BASED SEARCH AND MAXIMUM LIKELIHOOD ESTIMATION
Abstract
Simulation is one of the most commonly utilized modeling and analysis tools in both military and civilian settings. Simulation optimization aims to guide planning and decision making under uncertainty in these settings, frequently in dynamic settings. Our proposed research will address two practically important settings in simulation optimization, with the goal of developing new computationally efficient algorithms with provable convergence guarantees and to provide practical guidelines on implementation. Applications include path planning for unmanned aerial vehicles, as well as practical problems arising in battlefield simulations, neural computing and neuroimaging, supply chain management, and risk management/mitigation in finance and military scenarios.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 12, 2021
- Source ID
- FA95502010211
Entities
People
- Michael C. Fu
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Maryland