A new method for large-scale box constrained convex quadratic minimization problems

We propose a new adaptive and composite Barzilai–Borwein (BB) step size by integrating the advantages of such existing step sizes. Particularly, the proposed step size is an optimal weighted mean of two classical BB step sizes and the weights are updated at each iteration in accordance with the quality of the classical BB step sizes. Combined with the steepest descent direction, the adaptive and composite BB step size is incorporated into the development of an algorithm such that it is efficient to solve large-scale optimization problems. We prove that the developed algorithm is globally convergent and it R-linearly converges when applied to solve strictly convex quadratic minimization problems. Compared with the state-of-the-art algorithms available in the literature, the proposed step size is more efficient in solving ill-posed or large-scale benchmark test problems.

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A preconditioning algorithm for large-scale minimization problems

Tellus A Dynamic Meteorology and Oceanography ◽

10.3402/tellusa.v45i5.15048 ◽

1993 ◽

Vol 45 (5) ◽

pp. 478-492 ◽

Cited By ~ 5

Author(s):

Milija ŽUpanski

Keyword(s):

Large Scale ◽

Minimization Problems

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New Harvesting and Curing Techniques in the Production of Breeder's Seed Peanuts1

Peanut Science ◽

10.3146/i0095-3679-6-2-1 ◽

1979 ◽

Vol 6 (2) ◽

pp. 70-72

Author(s):

T. A. Coffelt ◽

F. S. Wright ◽

J. L. Steele

Keyword(s):

Large Scale ◽

Combine Method ◽

Frost Damage ◽

New Method ◽

Experimental Equipment ◽

Harvesting Method ◽

Curing Methods ◽

Labor Requirements ◽

High Level ◽

Varietal Purity

Abstract A new method of harvesting and curing breeder's seed peanuts in Virginia was initiated that would 1) reduce the labor requirements, 2) maintain a high level of germination, 3) maintain varietal purity at 100%, and 4) reduce the risk of frost damage. Three possible harvesting and curing methods were studied. The traditional stack-pole method satisfied the latter 3 objectives, but not the first. The windrow-combine method satisfied the first 2 objectives, but not the last 2. The direct harvesting method satisfied all four objectives. The experimental equipment and curing procedures for direct harvesting had been developed but not tested on a large scale for seed harvesting. This method has been used in Virginia to produce breeder's seed of 3 peanut varieties (Florigiant, VA 72R and VA 61R) during five years. Compared to the stackpole method, labor requirements have been reduced, satisfactory levels of germination and varietal purity have been obtained, and the risk of frost damage has been minimized.

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TreeMerge: a new method for improving the scalability of species tree estimation methods

Bioinformatics ◽

10.1093/bioinformatics/btz344 ◽

2019 ◽

Vol 35 (14) ◽

pp. i417-i426 ◽

Cited By ~ 7

Author(s):

Erin K Molloy ◽

Tandy Warnow

Keyword(s):

Large Scale ◽

Species Tree ◽

New Method ◽

Divide And Conquer ◽

Supplementary Information ◽

Estimation Methods ◽

Running Time ◽

Tree Estimation ◽

Computationally Intensive ◽

A Minor

Abstract Motivation At RECOMB-CG 2018, we presented NJMerge and showed that it could be used within a divide-and-conquer framework to scale computationally intensive methods for species tree estimation to larger datasets. However, NJMerge has two significant limitations: it can fail to return a tree and, when used within the proposed divide-and-conquer framework, has O(n5) running time for datasets with n species. Results Here we present a new method called ‘TreeMerge’ that improves on NJMerge in two ways: it is guaranteed to return a tree and it has dramatically faster running time within the same divide-and-conquer framework—only O(n2) time. We use a simulation study to evaluate TreeMerge in the context of multi-locus species tree estimation with two leading methods, ASTRAL-III and RAxML. We find that the divide-and-conquer framework using TreeMerge has a minor impact on species tree accuracy, dramatically reduces running time, and enables both ASTRAL-III and RAxML to complete on datasets (that they would otherwise fail on), when given 64 GB of memory and 48 h maximum running time. Thus, TreeMerge is a step toward a larger vision of enabling researchers with limited computational resources to perform large-scale species tree estimation, which we call Phylogenomics for All. Availability and implementation TreeMerge is publicly available on Github (http://github.com/ekmolloy/treemerge). Supplementary information Supplementary data are available at Bioinformatics online.

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A New Method Tracing Load-Deflection Equilibrium Path of a Doubly Nonlinear Truss

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.166-169.68 ◽

2012 ◽

Vol 166-169 ◽

pp. 68-72

Author(s):

Shu Tang Liu ◽

Qi Liang Long

Keyword(s):

Matrix Equation ◽

Stiffness Matrix ◽

Large Scale ◽

New Method ◽

Truss Structure ◽

Equilibrium Path ◽

Nodal Coordinates ◽

Doubly Nonlinear ◽

Global Stiffness Matrix

A new method tracing the load-deflection equilibrium path of a truss with doubly nonlinearity is proposed. The total global stiffness matrix equation has been formulated in terms of nodal coordinates, iteration formulations has been written through adopting a single control coordinate, so that an new method tracing the load-deflection equilibrium path has been proposed. Analysis results of Star dome truss and Schwedeler dome truss have shown that the proposed method is stable numerically, quick in convergence, high in degree of accuracy and easy in use. The proposed method can be used for large-scale truss structure.

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