Back to Top

Optimization Methods and Software (OMS)

Publisher :

Taylor and Francis Ltd.

Scopus Profile
Peer reviewed only
Scopus Profile
Open Access
  • Mathematics
  • Computer Science
  • Software
  • +2

e-ISSN :

1029-4937

Issue Frequency :

Bi-Monthly

p-ISSN :

1055-6788

Est. Year :

1992

Mobile :

4402080520500

Country :

United Kingdom

Language :

English

APC :

YES

Impact Factor Assignee :

Google Scholar

Email :

ulbrich@mathematik.tu-darmstadt.de

Journal Descriptions

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. 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.


Optimization Methods and Software (OMS) is :

International, Peer-Reviewed, Open Access, Refereed, Mathematics, Computer Science, Software, OPERATIONS RESEARCH, Management Science , Online or Print, Bi-Monthly Journal

UGC Approved, ISSN Approved: P-ISSN - 1055-6788, E-ISSN - 1029-4937, Established in - 1992, Impact Factor

Not Provide Crossref DOI

Indexed in Scopus, WoS

Not indexed in DOAJ, PubMed, UGC CARE

Publications of OMS

Parallel-batching machines scheduling problem with a truncated time-dependent learning effect via a hybrid CS-JADE algorithm

This research investigates the parallel-batching scheduling problems with a time-dependent learning effect where the job processing time is a decreasing function of its starting time. Both t...

Parallel algorithm portfolios with performance forecasting

We propose a novel algorithm portfolio model that incorporates time series forecasting techniques to predict online the performance of its constituent algorithms. The predictions are used to...

Establish Your Own Journal Without the Expense!

OJSCloud offers a complete, free setup to get you publishing.

Start Your Free Journal!
free profile