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Optimization and Engineering

International Multidisciplinary Journal to Promote Optimization Theory & Applications in Engineering Sciences

Optimization and Engineering promotes the advancement of optimization methods and the innovative application of optimization in engineering. It provides a forum where engineering researchers can obtain information about relevant new developments in optimization, and researchers in mathematical optimization can read about the successes of and opportunities for optimization in the various engineering fields. We encourage the submission of manuscripts that make a genuine mathematical optimization contribution to a challenging engineering problem.

  • Highlights successful applications of optimization in all engineering disciplines;

    Stimulates the development of novel optimization methods for challenging engineering problems;

    Promotes high-performance computational optimization techniques for data-driven engineering applications;

    Encompasses all mathematical optimization methods and algorithms relevant to engineering.

Journal information

Editor-in-Chief
  • Nikolaos V Sahinidis
Publishing model
Hybrid (Transformative Journal). How to publish with us, including Open Access

Journal metrics

2.619 (2021)
Impact factor
2.747 (2021)
Five year impact factor
113,684 (2021)
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Latest issue

Volume 24

Issue 1, March 2023

Special Issue dedicated to the 6th World Congress on Global Optimization held in Metz, France, July 8-10, 2019 and Optimization in Space Engineering

Latest articles

This journal has 123 open access articles
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Journal updates

  • Special Issue on Machine Learning and Inverse Problems

    Guest Editors: D. Auroux (Universite’ Cote d’Azur, France), V. Kovanis (Virginia Tech, USA), H. Kunze (University of Guelph, Canada), D. La Torre (SKEMA Business School, France)

    Submission deadline: November 30, 2023

    This special issue aims at bringing together articles that discuss recent advances in machine learning and inverse problems. Machine Learning is a subset of Artificial Intelligence focusing on computers’ ability to learn from data and to imitate intelligence human behaviour. A typical inverse problem seeks to find a mathematical model that admits given observational data as an approximate solution. Recent contributions in these areas aim at exploring potential synergies between their two different domains of research.  From one hand, in fact, machine learning algorithms can leverage large collections of training data to directly compute regularized reconstructions and estimate unknown parameters. From the other hand, machine learning algorithms can benefit from the vast inverse problem literature and the existing contributions to the theory of inverse problems, and they can be used to simulate boundary value data when they are missing.

  • Special Issue on Sustainable Development of Energy, Water and Environment Systems – SDEWES, dedicated to the SDEWES 2022 Conferences

    Guest editors: Dr. Marian Trafczynski (Warsaw University of Technology), Prof. Neven Duić (University of Zagreb), Prof. Krzysztof Urbaniec (Warsaw University of Technology), Dr. Hrvoje Mikulčić (Xi'an Jiaotong University/ University of Zagreb, Zagreb), Dr. Slawomir Alabrudzinski (Warsaw University of Technology).

    Submission Deadline: December 31, 2022

    The background of this Virtual Special Issue of the Optimization and Engineering journal are the 2022 Sustainable Development of Energy, Water and Environment Systems (SDEWES) Conferences. This broad field was discussed by the participants of three conferences held in 2022 – 3rd Latin American SDEWES Conference (Sao Paulo), 5th Southeast European SDEWES Conference (Vlorë) and 17th SDEWES Conference (Paphos).

  • Special Issue on "Optimization Methods in Inverse Problems and Applications to Science and Engineering"

    Guest Editors: H. Kunze (University of Guelph, Canada); D. La Torre (SKEMA Business School, France); and M. Ruiz-Galan (University of Granada, Spain)

    Submission deadline: May 31, 2021

    This special issue aims at bringing together articles that discuss recent advances of optimization methods and algorithms in inverse problems and application to science and engineering.  A typical inverse problem seeks to find a mathematical model that admits given observational data as an approximate solution. This sort of question is of great interest in many application areas, including biomedical engineering and imaging, remote sensing and seismic imaging, astronomy, oceanography, atmospheric sciences and meteorology, chemical engineering and material sciences, computer vision and image processing, ecology, economics, environmental systems, physical systems. Very often an inverse problem appears in the form of a parameter estimation problem, it can be formulated as an optimization model, and then solved using different optimization algorithms and techniques. All papers included in this special issue will consider aspects of numerical analysis, mathematical modeling, and computational methods.

  • Rosenbrock Prize

    Optimization and Engineering's Howard Rosenbrock Prize is awarded annually to honor the authors of the best paper published in the journal in the previous year.

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About this journal

Electronic ISSN
1573-2924
Print ISSN
1389-4420
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