Analysis of static simulated annealing algorithms

J. E. Orosz, S. H. Jacobson

Research output: Contribution to journalArticlepeer-review


Generalized hill climbing (GHC) algorithms provide a framework for modeling local search algorithms to address intractable discrete optimization problems. This paper introduces a measure for determining the expected number of iterations to visit a predetermined objective function level, given that an inferior objective function level has been reached in a finite number of iterations. A variation of simulated annealing (SA), termed static simulated annealing (S2A), is analyzed using this measure. S2A uses a fixed cooling schedule during the algorithm execution. Though S2A is probably nonconvergent, its finite-time performance can be assessed using the finite-time performance measure defined in this paper.

Original languageEnglish (US)
Pages (from-to)165-182
Number of pages18
JournalJournal of Optimization Theory and Applications
Issue number1
StatePublished - Oct 2002


  • Local search algorithms
  • cooling schedules
  • finite-time performance
  • simulated annealing

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Control and Optimization
  • Applied Mathematics


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