Simulated Annealing with Noisy or Imprecise Energy Measurements.

Abstract

The annealing algorithm (Ref. 1) is modified to allow for noisy or imprecise measurements of the energy cost function. This is important when the energy cannot be measured exactly or when it is computationally expensive to do so. Under suitable conditions on the noise/imprecision, it is shown that the modified algorithm exhibits the same convergence in probability to the globally minimum energy states as the annealing algorithm (Ref. 2). Since the annealing algorithm will typically enter and exit the minimum energy states infinitely often with probability one, the minimum energy state visited by the annealing algorithm is usually tracked. The effect of using noisy or imprecise energy measurements on tracking the minimum energy state visited by the modified algorithms is examined. Keywords: Simulated annealing, Combinatorial optimization, Noisy measurements, Markov chains, computer simulation. (kt)

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1989
Accession Number
ADA204553

Entities

People

  • S. B. Gelfand
  • Sanjoy K. Mitter

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Annealing
  • Computer Simulations
  • Computers
  • Convergence
  • Cooperation
  • Heuristic Methods
  • Markov Chains
  • Mathematics
  • Measurement
  • Optimization
  • Probability
  • Simulations
  • Simulators

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Mathematical Modeling and Probability Theory.