Parallel two-phase methods for global optimization on GPU
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Publication:1997322
DOI10.1016/j.matcom.2018.06.005OpenAlexW2812861060MaRDI QIDQ1997322
Ana M. Ferreiro, Carlos Vázquez, Eliana Costa e Silva, Aldina Correia, José A. García-Rodríguez
Publication date: 2 March 2021
Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.matcom.2018.06.005
Mathematical programming (90Cxx) Conference proceedings and collections of articles (00Bxx) Operations research, mathematical programming (90-XX)
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- Optimization by Simulated Annealing
- Implementing the Nelder-Mead simplex algorithm with adaptive parameters
- A hybrid simplex search and particle swarm optimization for unconstrained optimization
- On the limited memory BFGS method for large scale optimization
- Modification of the Wolfe line search rules to satisfy the descent condition in the Polak-Ribière-Polyak conjugate gradient method
- Generalized descent for global optimization
- Simulated annealing: Practice versus theory
- Handbook of global optimization. Vol. 2
- A magnetic resonance device designed via global optimization techniques
- On the multilevel structure of global optimization problems
- A deterministic algorithm for global optimization
- An efficient implementation of parallel simulated annealing algorithm in GPUs
- A particle swarm pattern search method for bound constrained global optimization
- Minimization of functions having Lipschitz continuous first partial derivatives
- SIMANN: A Global Optimization Algorithm using Simulated Annealing
- PSwarm: a hybrid solver for linearly constrained global derivative-free optimization
- Derivative-free optimization and filter methods to solve nonlinear constrained problems
- The Gradient Projection Method Using Curry’s Steplength
- `` Direct Search Solution of Numerical and Statistical Problems
- Direct Search Methods on Parallel Machines
- Global Convergence Properties of Conjugate Gradient Methods for Optimization
- Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions
- Convergence of the Nelder--Mead Simplex Method to a Nonstationary Point
- Line search algorithms with guaranteed sufficient decrease
- Hybrid simulated annealing and direct search method for nonlinear unconstrained global optimization
- Heuristic pattern search and its hybridization with simulated annealing for nonlinear global optimization
- Detection and Remediation of Stagnation in the Nelder--Mead Algorithm Using a Sufficient Decrease Condition
- A Limited Memory Algorithm for Bound Constrained Optimization
- Equation of State Calculations by Fast Computing Machines
- Function minimization by conjugate gradients
- An efficient method for finding the minimum of a function of several variables without calculating derivatives
- A Family of Variable-Metric Methods Derived by Variational Means
- The Convergence of a Class of Double-rank Minimization Algorithms
- A new approach to variable metric algorithms
- Conditioning of Quasi-Newton Methods for Function Minimization
- A Simplex Method for Function Minimization
- Local optima smoothing for global optimization
- Sequential Application of Simplex Designs in Optimisation and Evolutionary Operation