Aims and scope

The Journal of Optimization Theory and Applications is committed to publishing meticulously chosen, high-quality papers encompassing a range of contributions, including research papers, invited papers, survey papers, and technical notes. The content of the journal revolves around mathematical optimization techniques, computational methodologies of optimization algorithms, and their diverse applications in science, engineering, and business.

Theoretical domains covered in the journal include linear, nonlinear, conic, stochastic, discrete, and dynamic optimization, multiobjective optimization, optimal control, as well as variational and convex analysis. Application areas span mathematical economics, mathematical physics and biology, and various branches of engineering, including aerospace, biomedical, chemical, civil, electrical, and mechanical engineering. The journal encourages submissions in recent, emerging, and novel areas of optimization, such as machine/deep learning, artificial intelligence,  service systems optimization, and quantum computing optimization.

The Journal of Optimization Theory and Applications embraces a comprehensive approach, particularly embracing the application of rigorous optimization techniques in solving high impact problems. It provides a platform for book notices, and forums – the latter being concise papers facilitating comments on published works, discussions on open problems, and exploration of research perspectives. Through this diverse range of contributions, the journal aims to advance optimization sciences and their applications in various scientific and engineering domains.