Construct · 1 fields · 3 citations

simulated annealing: a standalone construct

One name. One construct. A landmark on the map.

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simulatedannealing1 CONSTRUCTSimulated annealingKIRKPATRICK · SA SEARCH

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Optimization and computer science

Stochastic global search that mimics slow cooling to escape local optima

Kirkpatrick, Gelatt, and Vecchi's 1983 Optimization by simulated annealing introduced and named this method for finding a near-optimal solution to a hard problem by imitating the slow cooling of a heated metal. The algorithm explores candidate solutions and accepts a worse one with a probability that shrinks as a control parameter called temperature is gradually lowered, so it can climb out of poor local optima while the temperature is high and then settle into a good solution as the temperature falls. Its acceptance rule is the Metropolis criterion from Metropolis, Rosenbluth, Rosenbluth, Teller, and Teller's 1953 study of equations of state, which simulated annealing repurposes from statistical physics into a general search procedure. Černý reached the same method independently in 1985 while attacking the traveling-salesman problem. Its scope is broad: the method needs only a way to score the cost of a candidate solution and a way to generate neighboring candidates, so one scheme applies across combinatorial and continuous optimization problems whose search space is riddled with local optima.[1][2][3]

Unit
One run of the search over a problem's space of candidate solutions
Recovery means
Not applicable
Measured by
Assessed by the cost or quality of the solution found and by the number of iterations or running time used, often against a defined cooling schedule

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Nearby constructs

annealing3 fields · 5 citationsjingle · one word, three constructstemperature4 fields · 4 citationsjingle · one word, four constructsheuristic4 fields · 4 citationsjingle · one word, four constructs

References

  1. Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598), 671–680. https://doi.org/10.1126/science.220.4598.671
  2. Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953). Equation of state calculations by fast computing machines. The Journal of Chemical Physics, 21(6), 1087–1092. https://doi.org/10.1063/1.1699114
  3. Černý, V. (1985). Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm. Journal of Optimization Theory and Applications, 45(1), 41–51. https://doi.org/10.1007/BF00940812

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