The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/24164726-614c-45ac-bcdc-a32f11119416

luo, wenjun (2023): Data underlying the paper: Two modified adaptive parameter conjugate gradient methods for unconstrained optimization. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/24164726-614c-45ac-bcdc-a32f11119416.v1

Dataset

• Numerical and Computational Mathematics
• Mathematical Sciences

conjugate gradient method

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by wenjun luo

This dataset contains data used for the article "Two modified adaptive parameter conjugate gradient methods for unconstrained optimization" Wenjun Luo, and Zezhong Wu.

MDYHS.csv and MDYHSCD.csv correspond to the MDYHS method and MDYHS method in the first class of methods proposed in this paper respectively.

CSDCG(O=1).csv, CSDCG(O=gg).csv, CSDCG(O=-sg).csv, and CSDCG(O=sy).csv respectively correspond to the cases of O=1, O=gg, O=-sg, and O=sy of the second method proposed in this paper.

ACGSSV.csv, ADHCG.csv, ADHCG.csv, and NACGM.csv are other CG methods for comparison.

where

--Problem Indicates the name of the problem in the CUTEest library

--Dims represent the dimension of the problem

--Method Indicates the method used to solve the problem

--x is the optimal solution

--Func is the value of the function at x

--Grad represents the infinite norm of the gradient of the function at x

--Nfunc represents the number of function evaluations

--Ngrad represents the number of gradient evaluation

--Iter represents the number of iterations

--Seconds indicate the running time

--StateCode indicates whether the status is abnormal, where 1 indicates success.

• 2023-05-09 first online, published, posted

4TU.ResearchData

*.csv

College of Applied Mathematics, Chengdu University of Information Technology