Generalized Simulated Annealing

By Y. Xiang, Sylvain Gubian, Florian Martin. 2017

335 citations recorded by the source corpus.

Many problems in mathematics, statistics, finance, biology, pharmacology, physics, applied mathematics, economics, and chemistry involve the determination of the global minimum of multidimensional real-valued functions. Simulated annealing methods have been widely used for different global optimization problems. Multiple versions of simulated annealing have been developed, including classical simulated annealing (CSA), fast simulated annealing (FSA), and generalized simulated annealing (GSA). After revisiting the basic idea of GSA using Tsallis statistics, we implemented a modified GSA approach using the R package GenSA. This package was designed to solve complicated nonlinear objective functions with a large number of local minima. In this chapter, we provide a brief introduction to this R package and demonstrate its utility by solving non-convexoptimization problems in different fields: physics, environmental science, and finance. We performed a comprehensive comparison between GenSA and other widely used R packages, including rgenoud and DEoptim. GenSA is useful and can provide a solution that is comparable with or even better than that provided by other widely used R packages for optimization.

Subfields: Artificial Intelligence, Economics and Econometrics, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/ea143047d0ed3f21f75d3a1b3b11cb041b4f450a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Klaus Schulten
2. R. Bernardi
3. Marc H. Taylor
4. Marcelo C. R. Melo
5. M. Wolff
6. T. Mildenberger

In Economics and Econometrics

1. Klaus Schulten
2. R. Bernardi
3. Marc H. Taylor
4. Marcelo C. R. Melo
5. M. Wolff
6. T. Mildenberger

In Statistical and Nonlinear Physics

1. Klaus Schulten
2. R. Bernardi
3. Marc H. Taylor
4. Marcelo C. R. Melo
5. M. Wolff
6. T. Mildenberger
7. Felix Ritort

Citations in the corpus

• Enhanced Sampling Techniques in Molecular Dynamics Simulations of Biological Systems (2014, positive): “In analogy to the tempering process (annealing) in metallurgy, where a molten metal is gradually cooled until it reaches a crystalline structure (global minimum), the simulated annealing methods depend on an artificial temperature [58] that decreases during the simulation.”
• TropFishR: an R package for fisheries analysis with length‐frequency data (2017, methodology): “107 The newly implemented ELEFAN method ‘ELEFAN_SA’ uses a simulated annealing algo108 rithm (Xiang et al. 2013) to solve for parameters of the VBGF.”