Decision-Theoretic Methods in Simulation Optimization
Abstract
Simulation optimization is the process of selecting the best among a collection of options, where each option can only be evaluated through stochastic simulation. A good simulation optimization algorithm enables finding the best option, or a very good option, in a reasonable amount of time. Because time is limited, the quality of the simulation optimization algorithm used can often determine whether we are able to discover a high quality option, or merely a mediocre one. The Department of Defense uses stochastic simulators to make a variety of critical strategic decisions, and good simulation optimization algorithms are critical to this decision-making process. The work in this project uses decision-theory to study and improve the decisions made by simulation optimization algorithms, providing algorithms for a number of distinct simulation optimization problems that improve performance over previous state-of-the-art algorithms.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 24, 2014
- Accession Number
- ADA610908
Entities
People
- Peter Frazier
Organizations
- Cornell University College of Engineering