Multiple-try simulated annealing algorithm for global optimization

DOI10.1155/2018/9248318zbMath1427.90235OpenAlexW2884994975MaRDI QIDQ1721625

Guangbao Guo, Wei Shao

Publication date: 8 February 2019

Published in: Mathematical Problems in Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2018/9248318

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Monte Carlo methods (65C05) Nonconvex programming, global optimization (90C26) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (1)

Computing the halfspace depth with multiple try algorithm and simulated annealing algorithm

Uses Software

• LBFGS-B

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Optimization by Simulated Annealing
• A note on the construction of blocked two-level designs with general minimum lower order confounding
• Computing power system parameters to maximize the small signal stability margin based on min-max models
• Levitin-Polyak well-posedness for optimization problems with generalized equilibrium constraints
• Equi-energy sampler with applications in statistical inference and statistical mechanics
• Interacting multiple try algorithms with different proposal distributions
• A superlinearly convergent projection method for constrained systems of nonlinear equations
• Asymptotics of the spectral gap with applications to the theory of simulated annealing
• Fast implementation of the Tukey depth
• Parallel and interacting stochastic approximation annealing algorithms for global optimisation
• Simulated annealing algorithm for optimal capital growth
• General notions of statistical depth function.
• Simulated annealing for higher dimensional projection depth
• On general minimum lower order confounding criterion for \(s\)-level regular designs
• An efficient proposal distribution for Metropolis-Hastings using a \(B\)-splines technique
• Finite sample breakdown point of Tukey's halfspace median
• Adaptive Lasso estimators for ultrahigh dimensional generalized linear models
• Parallel maximum likelihood estimator for multiple linear regression models
• Robust group non-convex estimations for high-dimensional partially linear models
• Parallel tempering for dynamic generalized linear models
• On constructing general minimum lower order confounding two-level block designs
• SCAD-Penalized Least Absolute Deviation Regression in High-Dimensional Models
• Advanced Markov Chain Monte Carlo Methods
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• Real-Parameter Evolutionary Monte Carlo With Applications to Bayesian Mixture Models
• Regression Depth
• The Multiple-Try Method and Local Optimization in Metropolis Sampling
• A semidefinite program approach for computing the maximum eigenvalue of a class of structured tensors and its applications in hypergraphs and copositivity test
• A Limited Memory Algorithm for Bound Constrained Optimization
• Simulated Stochastic Approximation Annealing for Global Optimization With a Square-Root Cooling Schedule
• Variable selection in the high-dimensional continuous generalized linear model with current status data
• Equation of State Calculations by Fast Computing Machines
• Simulated annealing for the bounds of Kendall's τ and Spearman's ρ
• Fractional Factorial Split-plot Designs with Two- and Four-level Factors Containing Clear Effects
• Stochastic Approximation in Monte Carlo Computation
• Computing Halfspace Depth and Regression Depth
• Monte Carlo sampling methods using Markov chains and their applications
• A Simplex Method for Function Minimization
• Convergence analysis of a block improvement method for polynomial optimization over unit spheres
• Monte Carlo strategies in scientific computing

This page was built for publication: Multiple-try simulated annealing algorithm for global optimization