This journal publishes research on the analysis and development of computational algorithms and modeling technology for optimization. It examines algorithms either for general classes of optimization problems or for more specific applied problems, stochastic algorithms as well as deterministic algorithms.

Computational Optimization and Applications covers a wide range of topics in optimization, including: large scale optimization, unconstrained optimization, constrained optimization, nondifferentiable optimization, combinatorial optimization, stochastic optimization, multiobjective optimization, and network optimization. It also covers linear programming, complexity theory, automatic differentiation, approximations and error analysis, parametric programming and sensitivity analysis, management science, and more.

This peer-reviewed journal features both research and tutorial papers that provide theoretical analysis, along with carefully designed computational experiments.


Officially cited as: Comput Optim Appl
  • Publishes research on the analysis and development of computational algorithms and modeling technology for optimization.
  • Examines algorithms either for general classes of optimization problems or for more specific applied problems, stochastic algorithms as well as deterministic algorithms.
  • Covers a wide range of topics in optimization.
Editor-in-Chief
  • William W. Hager
Publishing model
Hybrid. Open Choice – What is this?
Impact
Impact factor: 1.906 (2018)
Five year impact factor: 2.064 (2018)
Speed
Submission to first decision: 43 days
Acceptance to publication: 8 days
Usage
Downloads: 75,293 (2018)

Articles

Journal updates

  • COAP Best Paper Award

    Each year the Editorial Board of Computational Optimization and Applications selects a paper from the preceding year’s publications for the Best Paper Award.

View all updates

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About this journal

Electronic ISSN
1573-2894
Print ISSN
0926-6003
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