Taylor & Francis publishes 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 a clear potential for applicability, as well as successful applications of optimization methods and software in specific areas such as engineering, machine learning, data mining, economics, finance, biology, or medicine.

Peer Review Policy
All submitted manuscripts are subject to initial appraisal by the Editor. If found suitable for further consideration, papers are subject to peer review by independent, anonymous expert referees. All peer review is single blind and submissions can be made online at http://mc.manuscriptcentral.com/goms. 
Publishing Ethics
The Journal adheres to the highest standards of publishing ethics, with rigorous processes in place to ensure this is achieved.