Generalized Simulated Annealing

We propose a new stochastic algorithm (generalized simulated annealing) for computationally finding the global minimum of a given (not necessarily convex) energy/cost function defined in a continuous D-dimensional space. This algorithm recovers, as particular cases, the so called classical ("Boltzmann machine") and fast ("Cauchy machine") simulated annealings, and can be quicker than both. Key-words: simulated annealing; nonconvex optimization; gradient descent; generalized statistical mechanics.Comment: 13 pages, latex, 4 figures available upon request with the authors

Deconstructing Simulated Annealing

Recent advances in mobile information and self-learning information offer a viable alternative to interrupts. Here, we disprove the refinement of the producer-consumer problem, demonstrates the practical importance of operating systems. We verify that the UNIVAC computer and simulated annealing [14] can collaborate to answer this quagmire

Time series forecasting using a TSK fuzzy system tuned with simulated annealing

In this paper, a combination of a Takagi-Sugeno fuzzy system (TSK) and simulated annealing is used to predict well known time series by searching for the best configuration of the fuzzy system. Simulated annealing is used to optimise the parameters of the antecedent and the consequent parts of the fuzzy system rules. The results of the proposed method are encouraging indicating that simulated annealing and fuzzy logic are able to combine well in time series prediction

Simulated Annealing for Topological Solitons

The search for solutions of field theories allowing for topological solitons requires that we find the field configuration with the lowest energy in a given sector of topological charge. The standard approach is based on the numerical solution of the static Euler-Lagrange differential equation following from the field energy. As an alternative, we propose to use a simulated annealing algorithm to minimize the energy functional directly. We have applied simulated annealing to several nonlinear classical field theories: the sine-Gordon model in one dimension, the baby Skyrme model in two dimensions and the nuclear Skyrme model in three dimensions. We describe in detail the implementation of the simulated annealing algorithm, present our results and get independent confirmation of the studies which have used standard minimization techniques.Comment: 31 pages, LaTeX, better quality pics at http://www.phy.umist.ac.uk/~weidig/Simulated_Annealing/, updated for publicatio

Simulated Annealing for JPEG Quantization

JPEG is one of the most widely used image formats, but in some ways remains surprisingly unoptimized, perhaps because some natural optimizations would go outside the standard that defines JPEG. We show how to improve JPEG compression in a standard-compliant, backward-compatible manner, by finding improved default quantization tables. We describe a simulated annealing technique that has allowed us to find several quantization tables that perform better than the industry standard, in terms of both compressed size and image fidelity. Specifically, we derive tables that reduce the FSIM error by over 10% while improving compression by over 20% at quality level 95 in our tests; we also provide similar results for other quality levels. While we acknowledge our approach can in some images lead to visible artifacts under large magnification, we believe use of these quantization tables, or additional tables that could be found using our methodology, would significantly reduce JPEG file sizes with improved overall image quality.Comment: Appendix not included in arXiv version due to size restrictions. For full paper go to: http://www.eecs.harvard.edu/~michaelm/SimAnneal/PAPER/simulated-annealing-jpeg.pd