Hybrid Techniques for Optimizing Complex Systems

Abstract

This is the final technical report for a three year research project on Hybrid Techniques for Optimizing Complex Systems conducted at the University of Michigan, Ann Arbor and sponsored by the Air Force Research Laboratory. The project's overall goal was to investigate novel hybrid techniques that combine concepts from quantum and classical computer science to solve hard computational problems, including the handling of uncertainty. The research problems considered include design optimization and simulation of conventional CMOS and quantum systems, fault tolerance, resource allocation and scheduling, strategy optimization and related challenges facing the Air Force. The research focuses on accurate modeling of practical metrics of performance, robustness and cost, and their optimization in both linear and non-linear domains, using fast exact and heuristic methods, along with highly efficient data representations. Errors in data and control due to environmental effects, as well as uncertainty in the problem formulation, are taken into account during system modeling and optimization.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2009
Accession Number
ADA511428

Entities

People

  • Igor L. Markov
  • John P. Hayes

Organizations

  • University of Michigan

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Algorithms
  • Circuit Analysis
  • Computational Science
  • Computer Networks
  • Computer Science
  • Computers
  • Energy Consumption
  • Heuristic Methods
  • Information Processing
  • Ion Traps
  • Logic Gates
  • Mesh Networks
  • Network Topology
  • Quantum Computing
  • Quantum Information
  • Quantum Information Science

Readers

  • Computational Fluid Dynamics (CFD)
  • Operations Research
  • Research Science/Academic Research

Technology Areas

  • Quantum Computing