Engineering Optimization is an interdisciplinary journal that serves a vast technical community interested in quantitative computational methods of optimization. It emphasizes their practical applications across engineering disciplines including planning, design, manufacturing, and operational processes. The journal’s policy considers optimization as any formal numerical process aimed at enhancing technical performance and fostering innovation within engineering domains. While its primary focus lies on algorithms for numerical optimization, the journal also encourages submissions utilizing methodologies from operations research, decision support, statistical decision theory, systems theory, logical inference, knowledge-based systems, generative artificial intelligence, machine/deep learning, information theory, quantum computing, quantum information processing, and other cutting-edge techniques relevant to optimization in decision-making processes. For example, within the realm of artificial intelligence, the journal welcomes academic papers that explore how artificial intelligence methodologies enhance numerical optimization algorithms or propose innovative artificial intelligence methods to solve engineering optimization challenges.
Innovation in optimization is a fundamental requirement for all submissions, alongside a strong emphasis on engineering applicability. Engineering Optimization strives to encompass all disciplines within the engineering community, with main focus on environmental, civil, mechanical, manufacturing, aerospace, and industrial engineering. The journal invites papers that explore both theoretical research and practical industrial applications, demonstrating clear advancements in state-of-the-art formal optimization processes through innovative developments.
All submitted manuscripts undergo initial evaluation by the Editors. If deemed suitable for further consideration, they are subjected to peer review by independent, anonymous expert referees. The peer review process is single-blind, and submissions are managed through our Submission Portal.
Journal metrics
Usage
111K annual downloads/views
Citation metrics
2.2 (2023) Impact Factor
Q2 Impact Factor Best Quartile
2.3 (2023) 5 year IF
5.9 (2023) CiteScore (Scopus)
Q1 CiteScore Best Quartile
1.057 (2023) SNIP
0.621 (2023) SJR
Speed/acceptance
2 days avg. from submission to first
decision
65 days avg. from submission to first
post-review decision
25 days avg. from acceptance to online
publication
4% acceptance rate
Understanding and using journal metrics
Journal metrics can be a useful tool for readers, as well as for authors
who are deciding where to submit their next manuscript for publication.
However, any one metric only tells a part of the story of a journal’s
quality and impact. Each metric has its limitations which means that it
should never be considered in isolation, and metrics should be used to
support and not replace qualitative review.
We strongly recommend that you always use a number of metrics, alongside
other qualitative factors such as a journal’s aims & scope, its
readership, and a review of past content published in the journal. In
addition, a single article should always be assessed on its own merits and
never based on the metrics of the journal it was published in.
Usage and acceptance rate data above are for the last full calendar year
and are updated annually in February. Speed data is updated every six
months, based on the prior six months. Citation metrics are updated
annually mid-year. Please note that some journals do not display all of
the following metrics
(find out why).
Usage:
the total number of times articles in the journal were viewed by users
of Taylor & Francis Online in the previous calendar year, rounded to the
nearest thousand.
Citation Metrics
Impact Factor*:
the average number of citations received by articles published in the
journal within a two-year window. Only journals in the Clarivate Science
Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI),
Arts and Humanities Citation Index (AHCI) and the Emerging Sources
Citation Index (ESCI) have an Impact Factor.
Impact Factor Best Quartile*:
the journal’s highest subject category ranking in the Journal Citation
Reports. Q1 = 25% of journals with the highest Impact Factors.
5 Year Impact Factor*:
the average number of citations received by articles in the journal
within a five-year window.
CiteScore (Scopus)†:
the average number of citations received by articles in the journal over
a four-year period.
CiteScore Best Quartile†:
the journal’s highest CiteScore ranking in a Scopus subject category. Q1
= 25% of journals with the highest CiteScores.
SNIP
(Source Normalized Impact per Paper):
the number of citations per paper in the journal, divided by citation
potential in the field.
SJR
(Scimago Journal Rank):
Average number of (weighted) citations in one year, divided by the
number of articles published in the journal in the previous three years.
Speed/acceptance
From submission to first decision:
the average (median) number of days for a manuscript submitted to the
journal to receive a first decision. Based on manuscripts receiving a
first decision in the last six months.
From submission to first post-review decision:
the average (median) number of days for a manuscript submitted to the
journal to receive a first decision if it is sent out for peer review.
Based on manuscripts receiving a post-review first decision in the last
six months.
From acceptance to online publication:
the average (median) number of days from acceptance of a manuscript to
online publication of the Version of Record. Based on articles published
in the last six months.
Acceptance rate:
articles accepted for publication by the journal in the previous
calendar year as percentage of all papers receiving a final decision.
Editors-in-Chief Shu-Kai Fan, National Taipei University of Technology, Taiwan ( email) Francisco Luna, University of Málaga, Spain ( email)
Associate Editors Jan Blachut, University of Liverpool, UK Zong Woo Geem, Gachon University, South Korea José París, University of A Coruña, Spain Bruno Prata, Federal University of Ceará, Brazil Oliver Schütze, Cinvestav, Mexico Gary Wang, Simon Fraser University, Canada
Editorial Advisory Board Sujin Bureerat, Khon Kaen University, Thailand Gengdong Cheng, Dalian University of Technology, China Carlos A. C. Coello, Cinvestav-IPN, Mexico Kalyanmoy Deb, Michigan State University, USA Xiaoping Du, Purdue University, USA Ali Elkamel, University of Waterloo, Canada Kyriakos Giannakoglou, National Technical University of Athens, Greece Kazuhiro Izui, Kyoto University, Japan Sadan Kulturel-Konak, Penn State Berks, USA Kevin E. Lansey, University of Arizona, USA Farrokh Mistree, University of Oklahoma, USA Avi Ostfeld, Israel Institute of Technology, Israel Panos Y. Papalambros, University of Michigan, USA Ravipudi Venkata Rao, Sardar Vallabhbhai National Institute of Technology, India Tapabrata Ray, University of New South Wales, Australia Rommel G. Regis, Saint Joseph's University, USA Biswajit Sarkar, Yonsei University, South Korea Guangyong Sun, Hunan University, China M.-J. Tahk, Korea Advanced Institute of Science and Technology, South Korea Yu Liu, University of Electronic Science and Technology of China, China
Founding Editor-in-Chief Andrew B. Templeman, University of Liverpool, UK
Past Editors Andew B. Templeman, University of Liverpool, UK Ian C. Parmee, University of the West of England, UK
Abstracting and indexing
Engineering Optimization is indexed in:
British Library Chartered Association of Business Schools (CABS) Academic Journal Guide CLOCKSS CrossRef Current Contents: Engineering, Computing & Technology Google Scholar Ei Compendex (Engineering Village) Essential Science Indicators Microsoft Academic Portico Science Citation Index Expanded Scopus Ulrich's Periodicals Directory Web of Science WorldCat Local (OCLC)
Open access
Engineering Optimization is a hybrid open access journal that is part of our Open Select publishing program, giving you the option to publish open access. Publishing open access means that your article will be free to access online immediately on publication, increasing the visibility, readership, and impact of your research.
Why choose open access?
Increase the discoverability and readership of your article
Make an impact and reach new readers, not just those with easy access to a research library
Freely share your work with anyone, anywhere
Comply with funding mandates and meet the requirements of your institution, employer or funder
Rigorous peer review for every open access article
Article Publishing Charges (APC)
If you choose to publish open access in this journal you may be asked to pay an Article Publishing Charge (APC). You may be able to publish your article at no cost to yourself or with a reduced APC if your institution or research funder has an open access agreement or membership with Taylor & Francis.
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