Simulated annealing: Practice versus theory
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TLDR
Using the author's Adaptive Simulated Annealing (ASA) code, some examples are given which demonstrate how SQ can be much faster than SA without sacrificing accuracy.About:
This article is published in Mathematical and Computer Modelling.The article was published on 1993-12-01 and is currently open access. It has received 1128 citations till now. The article focuses on the topics: Adaptive simulated annealing & Simulated annealing.read more
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Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
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Restoring low resolution structure of biological macromolecules from solution scattering using simulated annealing.
TL;DR: Application of the method is illustrated by the restoration of a ribosome-like model structure and more realistically by the determination of the shape of several proteins from experimental x-ray scattering data.
Book
Elements of artificial neural networks
TL;DR: This paper presents a meta-modelling framework that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of supervised learning of neural networks.
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Global rigid body modeling of macromolecular complexes against small-angle scattering data
TL;DR: New methods to automatically build models of macromolecular complexes from high-resolution structures or homology models of their subunits or domains against x-ray or neutron small-angle scattering data are presented and allow one to construct interconnected models without steric clashes.
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Metaheuristics: A bibliography
Ibrahim H. Osman,Gilbert Laporte +1 more
TL;DR: This bibliography provides a classification of a comprehensive list of 1380 references on the theory and application of metaheuristics that have had widespread successes in attacking a variety of difficult combinatorial optimization problems that arise in many practical areas.
References
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Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
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Equation of state calculations by fast computing machines
TL;DR: In this article, a modified Monte Carlo integration over configuration space is used to investigate the properties of a two-dimensional rigid-sphere system with a set of interacting individual molecules, and the results are compared to free volume equations of state and a four-term virial coefficient expansion.
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Adaptation in natural and artificial systems
TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
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Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
Stuart Geman,Donald Geman +1 more
TL;DR: The analogy between images and statistical mechanics systems is made and the analogous operation under the posterior distribution yields the maximum a posteriori (MAP) estimate of the image given the degraded observations, creating a highly parallel ``relaxation'' algorithm for MAP estimation.
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Monte Carlo Sampling Methods Using Markov Chains and Their Applications
TL;DR: A generalization of the sampling method introduced by Metropolis et al. as mentioned in this paper is presented along with an exposition of the relevant theory, techniques of application and methods and difficulties of assessing the error in Monte Carlo estimates.