Accelerating Convergence of Free Energy Computations with Hamiltonian Simulated Annealing of Solvent (HSAS)
نویسندگان
چکیده
منابع مشابه
On the convergence of Parallel Simulated Annealing
Using the Matrix-Tree Theorem and coupling methods the convergence of the Parallel Chain (PC) algorithm to the set of global minima is established for various selection functions. It is illustrated that there may be convergence to a set of non-global minima when selecting one of the best states (Best-Wins strategy). In the latter case the convergence of the homogeneous PC algorithm is proved fo...
متن کاملOn the Convergence Time of Simulated Annealing
Simulated Annealing is a family of randomized algorithms used to solve many combinatorial optimization problems. In practice they have been applied to solve some presumably hard (e.g., NP-complete) problems. The level of performance obtained has been promised [5, 2, 6, 14]. The success of its heuristic technique has motivated analysis of this algorithm from a theoretical point of view. In parti...
متن کاملConvergence of Gibbs Measures Associated with Simulated Annealing
We start with an explanation of Simulated Annealing. In order to do this, we quote the paper “Convergence of Gibbs Measures Associated with Simulated Annealing” [CHK], by professors Dennis Cox of the Rice University Statistics department, Robert Hardt of the Rice University Mathematics department, and Petr Klouček of the University of Houston Texas Learning and Computation Center, which states ...
متن کاملSimulated annealing with asymptotic convergence for nonlinear constrained optimization
In this paper, we present constrained simulated annealing (CSA), an algorithm that extends conventional simulated annealing to look for constrained local minima of nonlinear constrained optimization problems. The algorithm is based on the theory of extended saddle points (ESPs) that shows the one-to-one correspondence between a constrained local minimum and anESP of the corresponding penalty fu...
متن کاملSimulated Annealing with Asymptotic Convergence for Nonlinear Constrained Global Optimization
In this paper, we present constrained simulated annealing (CSA), a global minimization algorithm that converges to constrained global minima with probability one, for solving nonlinear discrete nonconvex constrained minimization problems. The algorithm is based on the necessary and sufficient condition for constrained local minima in the theory of discrete Lagrange multipliers we developed earl...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Chemical Theory and Computation
سال: 2019
ISSN: 1549-9618,1549-9626
DOI: 10.1021/acs.jctc.8b01147