Journal of Optimization Theory and Applications

The Journal of Optimization Theory and Applications publishes carefully selected papers covering mathematical optimization techniques and their applications to science and engineering. An applications paper should cover the application of an optimization technique along with the solution of a particular problem.

Typical theoretical areas in the journal include linear, nonlinear, conic, stochastic, discrete, and dynamic optimization, variational and convex analysis. Application areas comprise of mathematical economics, mathematical physics and biology, and aerospace, biomedical, chemical, civil, electrical, and mechanical engineering. Recent, emerging, and novel areas of optimization, such machine/deep learning, service systems optimization and quantum computing optimization are encouraged.

The Journal of Optimization Theory and Applications journal publishes six types of contributions: regular papers, invited papers, survey papers, technical notes, book notices, and forums (very short papers containing comments on published papers, discussions of open problems, discussions of research perspectives, and so on).