Journal Information
Journal of Optimization Theory and Applications
https://link.springer.com/journal/10957
Impact Factor:
1.600
Publisher:
Springer
ISSN:
0022-3239
Viewed:
13918
Tracked:
1
Call For Papers
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.
Last updated by Dou Sun in 2024-07-20
Special Issues
Special Issue on Generalized Convexity, Monotonicity, Variational Analysis and Applications
Submission Date: 2025-03-31

In recent decades, researchers have increasingly tackled with optimization challenges that defy resolution through conventional convex or monotonic frameworks, in view of applications in science, engineering and other disciplines. Consequently, novel methodologies are emerging in nonsmooth, variational, and convex analysis. This special issue aims to publish original high-quality papers centered around the broad area of convexity, monotonicity and their extensions, and variational analysis, in and beyond optimization. Thus, it sheds new light on classical results and opens new approaches to face ‘‘nonconvex problems’’ in both theoretical and practical scenarios. Some of the papers collected in the special issue will be presented at the XIV International Symposium on Generalized Convexity and Monotonicity, to be held on September 2-6, 2024, in Pisa, Italy. So that, other researchers working in the area will also be welcome to contribute. Contributions may include, but are not limited to the following topics: * Algorithms for fixed point, (quasi-) variational inequality and optimization problems; * Quadratic optimization problems; * (Quasi-) Variational inequalities, equilibrium problems and related topics; * Robust optimization; * Set optimization; * Vector optimization. Timing: Submission deadline: March 31, 2025 Targeted Publication Date: December 2025
Last updated by Dou Sun in 2024-07-20
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