Optimization Methods & Software

杂志介绍

Optimization Methods & Software杂志介绍

《Optimization Methods & Software》是一本以English为主的未开放获取国际优秀期刊，中文名称优化方法和软件，本刊主要出版、报道数学-COMPUTER SCIENCE, SOFTWARE ENGINEERING领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为1.4，最新CiteScore 指数为4.5。

本刊近期中国学者发表的论文主要有：

• 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

英文介绍

Optimization Methods & Software杂志英文介绍

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.