雜志介紹

Optimization Methods & Software雜志介紹

《Optimization Methods & Software》是一本以English為主的未開(kāi)放獲取國(guó)際優(yōu)秀期刊，中文名稱(chēng)優(yōu)化方法和軟件，本刊主要出版、報(bào)道數(shù)學(xué)-COMPUTER SCIENCE, SOFTWARE ENGINEERING領(lǐng)域的研究動(dòng)態(tài)以及在該領(lǐng)域取得的各方面的經(jīng)驗(yàn)和科研成果，介紹該領(lǐng)域有關(guān)本專(zhuān)業(yè)的最新進(jìn)展，探討行業(yè)發(fā)展的思路和方法，以促進(jìn)學(xué)術(shù)信息交流，提高行業(yè)發(fā)展。該刊已被國(guó)際權(quán)威數(shù)據(jù)庫(kù)SCIE收錄，為該領(lǐng)域相關(guān)學(xué)科的發(fā)展起到了良好的推動(dòng)作用，也得到了本專(zhuān)業(yè)人員的廣泛認(rèn)可。該刊最新影響因子為1.4，最新CiteScore 指數(shù)為4.5。

本刊近期中國(guó)學(xué)者發(fā)表的論文主要有：

• An efficient semismooth Newton method for adaptive sparse signal recovery problems

  Author: Ding, Yanyun; Zhang, Haibin; Li, Peili; Xiao, Yunhai

• Non-convex regularization and accelerated gradient algorithm for sparse portfolio selection

  Author: Li, Qian; Zhang, Wei; Wang, Guoqiang; Bai, Yanqin

• Properties of semi-conjugate gradient methods for solving unsymmetric positive definite linear systems

  Author: Huang, Na; Dai, Yu-Hong; Orban, Dominique; Saunders, Michael A.

• Exact penalization for cardinality and rank-constrained optimization problems via partial regularization

  Author: Lu, Zhaosong; Li, Xiaorui; Xiang, Shuhuang

英文介紹

Optimization Methods & Software雜志英文介紹

Optimization Methods and Software

publishes refereed papers on the latest developments in the theory and realization of optimization methods, with particular emphasis on the interface between software development and algorithm design.

Topics include:

Theory, implementation and performance evaluation of algorithms and computer codes for linear, nonlinear, discrete, stochastic optimization and optimal control. This includes in particular conic, semi-definite, mixed integer, network, non-smooth, multi-objective and global optimization by deterministic or nondeterministic algorithms.

Algorithms and software for complementarity, variational inequalities and equilibrium problems, and also for solving inverse problems, systems of nonlinear equations and the numerical study of parameter dependent operators.

Various aspects of efficient and user-friendly implementations: e.g. automatic differentiation, massively parallel optimization, distributed computing, on-line algorithms, error sensitivity and validity analysis, problem scaling, stopping criteria and symbolic numeric interfaces.

Theoretical studies with clear potential for applications and successful applications of specially adapted optimization methods and software to fields like engineering, machine learning, data mining, economics, finance, biology, or medicine. These submissions should not consist solely of the straightforward use of standard optimization techniques.