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Optimization and Engineering

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

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Please note this journal’s peer review system has changed, it now uses Snapp (Springer Nature’s Article Processing Platform). See the journal updates page for more information.

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.

Editor-in-Chief
  • Michael Ulbrich
Impact factor
2.1 (2022)
5 year impact factor
2.4 (2022)
Submission to first decision (median)
10 days
Downloads
203,224 (2023)

Latest issue

March 2024 |

Volume 25, Issue 1

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

Latest articles

Journal updates

  • Special Issue on Graph Theory-based Approaches for Optimizing Neural Network Architectures

    Guest Editors: Dr. Jia-Bao Liu (Anhui Jianzhu University, China), Dr. Muhammad Javaid (University of Management and Technology, Pakistan), Dr. Mohammad Reza Farahani (Iran University of Science and Technology, Iran)

    Submission Deadline: February 08, 2024

    This special issue aims at bringing together articles that discuss recent advances in Graph Theory-based Approaches for Optimizing Neural Network Architectures. Graph theory has emerged as a powerful tool for optimizing neural network architectures. As the field of artificial intelligence continues to advance, researchers and engineers look for innovative methods to design more efficient and effective neural networks. Exploiting graph theory principles can address challenges related to model complexity, training efficiency and generalization capabilities. In Neural networks, especially deep learning models have demonstrated remarkable success in various tasks such as image recognition, natural language processing and speech synthesis. However, the increased complexity of these models comes with a trade-off. Graph theory provides a framework for modeling neural networks as graphs provided with neurons as nodes and connections as edges. We encourage submissions from researchers in this background to demonstrate the effectiveness of graph theory-based approaches on various benchmark datasets and real-world applications.

  • 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).

Journal information

Electronic ISSN
1573-2924
Print ISSN
1389-4420
Abstracted and indexed in
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  7. Current Contents/Engineering, Computing and Technology
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  11. Google Scholar
  12. INIS Atomindex
  13. INSPEC
  14. Japanese Science and Technology Agency (JST)
  15. Mathematical Reviews
  16. Naver
  17. OCLC WorldCat Discovery Service
  18. Portico
  19. ProQuest
  20. SCImago
  21. SCOPUS
  22. Science Citation Index Expanded (SCIE)
  23. TD Net Discovery Service
  24. UGC-CARE List (India)
  25. Wanfang
  26. zbMATH
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