Definition
Very fast simulated reannealing (VFSR) is an improved version of simulated annealing (SA). The latter is a global optimization method suitable for complex, non-convex problems. It aims to optimize an objective function ℋ(x), with respect to the D-dimensional parameter vector x = (x1, …xD)⊤. Simulated annealing relies on random Metropolis sampling of the parameter space which mimics the physical annealing process of materials. The annealing algorithm treats ℋ(x) as a fictitious energy function. The algorithm proposes moves which change the current state x, seeking for the optimum state. The proposed states are controlled by an internal parameter which plays the role of temperature and controls the acceptance rate of the proposed states.
Very fast simulated reannealing employs a fast temperature reduction schedule in combination with periodic resetting of the annealing temperature to higher values. In addition, it allows different temperatures for different parameters, and an...
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Abbreviations
- ASA:
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Adaptive simulated annealing
- SA:
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Simulated annealing
- SQ:
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Simulated quenching
- VFSR:
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Very fast simulated reannealing
Bibliography
Chen S, Luk BL (1999) Adaptive simulated annealing for optimization in signal processing applications. Signal Process 79(1):117–128. https://doi.org/10.1016/S0165-1684(99)00084-5
Geman S, Geman D (1984) Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Trans Pattern Anal Mach Intell 6(6):721–741. https://doi.org/10.1109/TPAMI.1984.4767596
Hristopulos DT (2020) Random fields for spatial data modeling: a primer for scientists and engineers. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-1918-4
Iglesias-Marzoa R, López-Morales M, Arévalo Morales MJ (2015) The rvfit code: a detailed adaptive simulated annealing code for fitting binaries and exoplanets radial velocities. Publ Astron Soc Pac 127(952):567–582. https://doi.org/10.1086/682056
Ingber L (1989) Very fast simulated re-annealing. Math Comput Model 12(8):967–973. https://doi.org/10.1016/0895-7177(89)90202-1
Ingber L (2012) Adaptive simulated annealing. In: Hime A, Ingber L, Petraglia A, Petraglia MR, Machado MAS (eds) Stochastic global optimization and its applications with fuzzy adaptive simulated annealing. Springer, Heidelberg, pp 33–62. https://doi.org/10.1007/978-3-642-27479-4
Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E (1953) Equation of state calculations by fast computing machines. J Chem Phys 21(6):1087–1092. https://doi.org/10.1063/1.1699114
Pyrcz MJ, Deutsch CV (2014) Geostatistical reservoir modeling, 2nd edn. Oxford University Press, New York
Salamon P, Sibani P, Frost R (2002) Facts, conjectures, and improvements for simulated annealing. SIAM monographs on mathematical modeling and computation, SIAM, Philadelphia. https://doi.org/10.1137/1.9780898718300
Sen MK, Stoffa PL (1996) Bayesian inference, Gibbs’ sampler and uncertainty estimation in geophysical inversion. Geophys Prospect 44(2):313–350. https://doi.org/10.1111/j.1365-2478.1996.tb00152.x
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Hristopulos, D.T. (2022). Very Fast Simulated Reannealing. In: Daya Sagar, B., Cheng, Q., McKinley, J., Agterberg, F. (eds) Encyclopedia of Mathematical Geosciences. Encyclopedia of Earth Sciences Series. Springer, Cham. https://doi.org/10.1007/978-3-030-26050-7_345-1
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DOI: https://doi.org/10.1007/978-3-030-26050-7_345-1
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Very Fast Simulated Reannealing- Published:
- 05 August 2022
DOI: https://doi.org/10.1007/978-3-030-26050-7_345-2
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Very Fast Simulated Reannealing- Published:
- 29 January 2022
DOI: https://doi.org/10.1007/978-3-030-26050-7_345-1